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Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Website: https://www.edureka.co/data-science Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 77758 edureka!
Data Mining: How You're Revealing More Than You Think
 
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Data mining recently made big news with the Cambridge Analytica scandal, but it is not just for ads and politics. It can help doctors spot fatal infections and it can even predict massacres in the Congo. Hosted by: Stefan Chin Head to https://scishowfinds.com/ for hand selected artifacts of the universe! ---------- Support SciShow by becoming a patron on Patreon: https://www.patreon.com/scishow ---------- Dooblydoo thanks go to the following Patreon supporters: Lazarus G, Sam Lutfi, Nicholas Smith, D.A. Noe, سلطان الخليفي, Piya Shedden, KatieMarie Magnone, Scott Satovsky Jr, Charles Southerland, Patrick D. Ashmore, Tim Curwick, charles george, Kevin Bealer, Chris Peters ---------- Looking for SciShow elsewhere on the internet? Facebook: http://www.facebook.com/scishow Twitter: http://www.twitter.com/scishow Tumblr: http://scishow.tumblr.com Instagram: http://instagram.com/thescishow ---------- Sources: https://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/1230 https://www.theregister.co.uk/2006/08/15/beer_diapers/ https://www.theatlantic.com/technology/archive/2012/04/everything-you-wanted-to-know-about-data-mining-but-were-afraid-to-ask/255388/ https://www.economist.com/node/15557465 https://blogs.scientificamerican.com/guest-blog/9-bizarre-and-surprising-insights-from-data-science/ https://qz.com/584287/data-scientists-keep-forgetting-the-one-rule-every-researcher-should-know-by-heart/ https://www.amazon.com/Predictive-Analytics-Power-Predict-Click/dp/1118356853 http://dml.cs.byu.edu/~cgc/docs/mldm_tools/Reading/DMSuccessStories.html http://content.time.com/time/magazine/article/0,9171,2058205,00.html https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all&_r=0 https://www2.deloitte.com/content/dam/Deloitte/de/Documents/deloitte-analytics/Deloitte_Predictive-Maintenance_PositionPaper.pdf https://www.cs.helsinki.fi/u/htoivone/pubs/advances.pdf http://cecs.louisville.edu/datamining/PDF/0471228524.pdf https://bits.blogs.nytimes.com/2012/03/28/bizarre-insights-from-big-data https://scholar.harvard.edu/files/todd_rogers/files/political_campaigns_and_big_data_0.pdf https://insights.spotify.com/us/2015/09/30/50-strangest-genre-names/ https://www.theguardian.com/news/2005/jan/12/food.foodanddrink1 https://adexchanger.com/data-exchanges/real-world-data-science-how-ebay-and-placed-put-theory-into-practice/ https://www.theverge.com/2015/9/30/9416579/spotify-discover-weekly-online-music-curation-interview http://blog.galvanize.com/spotify-discover-weekly-data-science/ Audio Source: https://freesound.org/people/makosan/sounds/135191/ Image Source: https://commons.wikimedia.org/wiki/File:Swiss_average.png
Views: 151546 SciShow
Extract Structured Data from unstructured Text (Text Mining Using R)
 
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A very basic example: convert unstructured data from text files to structured analyzable format.
Views: 13670 Stat Pharm
The Best Way to Prepare a Dataset Easily
 
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In this video, I go over the 3 steps you need to prepare a dataset to be fed into a machine learning model. (selecting the data, processing it, and transforming it). The example I use is preparing a dataset of brain scans to classify whether or not someone is meditating. The challenge for this video is here: https://github.com/llSourcell/prepare_dataset_challenge Carl's winning code: https://github.com/av80r/coaster_racer_coding_challenge Rohan's runner-up code: https://github.com/rhnvrm/universe-coaster-racer-challenge Come join other Wizards in our Slack channel: http://wizards.herokuapp.com/ Dataset sources I talked about: https://github.com/caesar0301/awesome-public-datasets https://www.kaggle.com/datasets http://reddit.com/r/datasets More learning resources: https://docs.microsoft.com/en-us/azure/machine-learning/machine-learning-data-science-prepare-data http://machinelearningmastery.com/how-to-prepare-data-for-machine-learning/ https://www.youtube.com/watch?v=kSslGdST2Ms http://freecontent.manning.com/real-world-machine-learning-pre-processing-data-for-modeling/ http://docs.aws.amazon.com/machine-learning/latest/dg/step-1-download-edit-and-upload-data.html http://paginas.fe.up.pt/~ec/files_1112/week_03_Data_Preparation.pdf Please subscribe! And like. And comment. That's what keeps me going. And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/ Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 191587 Siraj Raval
Data Mining Lecture - - Data Analytics life cycle (Eng-Hindi)
 
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Business Intelligence Big data issues are solved using data analytics life cycle The key roles of data analytics are explained -~-~~-~~~-~~-~- Please watch: "PL vs FOL | Artificial Intelligence | (Eng-Hindi) | #3" https://www.youtube.com/watch?v=GS3HKR6CV8E -~-~~-~~~-~~-~-
Views: 22706 Well Academy
Learn Data Science in 3 Months
 
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I've created a 3 month curriculum to help you go from absolute beginner to proficient in the art of data science! This open source curriculum consists of purely free resources that I’ve compiled from across the Web and has no prerequisites, you don’t even have to have coded before. I’ve designed it for anyone who wants to improve their skills and find paid work ASAP, ether through a full-time position or contract work. You’ll be learning a host of tools like SQL, Python, Hadoop, and even data storytelling, all of which make up the complete data science pipeline. Curriculum for this video: https://github.com/llSourcell/Learn_Data_Science_in_3_Months Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Week 1 - Learn Python - EdX https://www.edx.org/course/introduction-python-data-science-2 - Siraj Raval https://www.youtube.com/watch?v=T5pRlIbr6gg&list=PL2-dafEMk2A6QKz1mrk1uIGfHkC1zZ6UU Week 2 - Statistics & Probability - KhanAcademy https://www.khanacademy.org/math/statistics-probability Week 3 - Data Pre-processing, Data Vis, Exploratory Data Analysis - EdX https://www.edx.org/course/introduction-to-computing-for-data-analysis Week 4 - Kaggle Project #1 Week 5-6 - Algorithms & Machine Learning - Columbia https://courses.edx.org/courses/course-v1:ColumbiaX+DS102X+2T2018/course/ Week 7 - Deep Learning - Part 1 and 2 of DL Book https://www.deeplearningbook.org/ - Siraj Raval https://www.youtube.com/watch?v=vOppzHpvTiQ&list=PL2-dafEMk2A7YdKv4XfKpfbTH5z6rEEj3 Week 8 - Kaggle Project #2 Week 9 - Databases (SQL + NoSQL) - Udacity https://www.udacity.com/course/intro-to-relational-databases--ud197 - EdX https://www.edx.org/course/introduction-to-nosql-data-solutions-2 Week 10 - Hadoop & Map Reduce + Spark - Udacity https://www.udacity.com/course/intro-to-hadoop-and-mapreduce--ud617 - Spark Workshop https://stanford.edu/~rezab/sparkclass/slides/itas_workshop.pdf Week 11 - Data Storytelling - Edx https://www.edx.org/course/analytics-storytelling-impact-1 Week 12- Kaggle Project #3 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hiring? Need a Job? See our job board!: www.theschool.ai/jobs/ Need help on a project? See our consulting group: www.theschool.ai/consulting-group/ Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 302917 Siraj Raval
DATA SCIENCE FREE BOOKS ONLINE | DOWNLOAD YOUR COPY
 
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Here's a list of 10 must read book on Data Science & Machine Learning. Foundations of DATA SCIENCE Book www.cs.cornell.edu/jeh/book.pdf Understanding Machine Learning Book www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf The Elements of Statistical Learning Book web.stanford.edu/~hastie/Papers/ESLII.pdf An Introduction to Statistical Learning Book www-bcf.usc.edu/~gareth/ISL/ISLR%20First%20Printing.pdf Mining of Massive Data Sets Book infolab.stanford.edu/~ullman/mmds/book.pdf
Views: 2113 DATA SCIENCE
STRUCTURED and UNSTRUCTURED DATA analysis and management methods in big data database with examples
 
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In this video we wil learn about structured data and unstructured data. Furthur more we will learn unstructured data,structured and unstructured data,unstructured data analysis,unstructured data management,structured unstructured data,unstructured data analysis methods,unstructured database,structured data and unstructured data,big data structured and unstructured,structured and unstructured data examples,structured and unstructured data in big data,big data unstructured,structured semi structured and unstructured data,unstructured data database. -~-~~-~~~-~~-~- Please watch: "Best Quotation Websites" https://www.youtube.com/watch?v=5UzYlULfLSQ -~-~~-~~~-~~-~-
Cure Algorithm in Hindi | Big data analytics Tutorials
 
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visit our website for full course www.lastmomenttuitions.com NOTES: https://lastmomenttuitions.com/how-to-buy-notes/ Any doubt ask us and connect us at : you can connect us at Gmail:[email protected] you can email us :[email protected] Whatsapp contact:9762903078 facebook: https://www.facebook.com/lastmomenttu... more videos coming soon subscribe karke rakho tab tak
Views: 11415 Last moment tuitions
PDF Data Scraping
 
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Automated web scraping services provide fast data acquirement in structured format. No matter if used for big data, data mining, artificial intelligence, machine learning or business intelligence applications. The scraped data come from various sources and forms. It can be websites, various databases, XML feeds and CSV, TXT or XLS file formats for example. Billions of PDF files stored online form a huge data library worth scraping. Have you ever tried to get any data from various PDF files? Then you know how panful it is. We have created an algorithm that allows you to extract data in an easily readable structured way. With PDFix we can recognize all logical structures and we can give you a hierarchical structure of document elements in a correct reading order. With the PDFix SDK we believe your web crawler can be programmed to access the PDF files and: - Search Text inside PDFs – you can find and extract specific information - Detect and Export Tables - Extract Annotations - Detect and Extract Related Images - Use Regular Expression, Pattern Matching - Detect and Scrape information from Charts Structured format You will need the scraped data from PDFs in various formats. With the PDFix you will get a structured output in: - CSV - HTML - XML - JSON
Views: 804 Team PDFix
Introduction to Data Science with R - Data Analysis Part 1
 
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Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 1018274 David Langer
Text Mining in R Tutorial: Term Frequency & Word Clouds
 
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This tutorial will show you how to analyze text data in R. Visit https://deltadna.com/blog/text-mining-in-r-for-term-frequency/ for free downloadable sample data to use with this tutorial. Please note that the data source has now changed from 'demo-co.deltacrunch' to 'demo-account.demo-game' Text analysis is the hot new trend in analytics, and with good reason! Text is a huge, mainly untapped source of data, and with Wikipedia alone estimated to contain 2.6 billion English words, there's plenty to analyze. Performing a text analysis will allow you to find out what people are saying about your game in their own words, but in a quantifiable manner. In this tutorial, you will learn how to analyze text data in R, and it give you the tools to do a bespoke analysis on your own.
Views: 68193 deltaDNA
More Data Mining with Weka (1.6: Working with big data)
 
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More Data Mining with Weka: online course from the University of Waikato Class 1 - Lesson 6: Working with big data http://weka.waikato.ac.nz/ Slides (PDF): http://goo.gl/Le602g https://twitter.com/WekaMOOC http://wekamooc.blogspot.co.nz/ Department of Computer Science University of Waikato New Zealand http://cs.waikato.ac.nz/
Views: 10533 WekaMOOC
Exploratory Data Analysis (EDA) Using Python (Jupyter Notebook)
 
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In this video you will learn how to perform Exploratory Data Analysis using Python. We will see how to slice data using Pandas, how to perform computing summary statistics using Numpy and how to vizualise data using Matplotlib and Seaborn. Exploratory data analysis is very usefull while building Statistical/Machine Learning models. It helps to understand the structure of the data in order to be able to build a good predictive model ANalytics Study Pack : http://analyticuniversity.com/ Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 9355 Analytics University
What is data science In telugu  - డేటా సైన్స్ అంటే ఏమిటి -9059868766 Artificial intelligence AI Demo
 
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data science training python videos, datacamp data science python, intro to python for data science course by datacamp, python data science course, python data science tutorial, python for data science book, python for data science pdf, python training videos, youtube python data science, What is data science In telugu - డేటా సైన్స్ అంటే ఏమిటి Download data science content Pdf https://goo.gl/JN6iGs http://www.sivaitsoft.com/data-science-online-training-kukatpally/ What is data science course? What is a data scientist? Who coined data science? What is big data analysis? Data Science course content vlrtraining 9059868766 Hyderabad https://goo.gl/JN6iGs DATA SCIENCE ONLINE TRAINING Data Science Online Training kukatpally Hyderabad provided by VLR Trainings. Data Science is that the study ofDATA SCIENCE Online training wherever data comes from, what it represents and the way it is became a valuable resource in the creation of business and IT ways. More info Wikipedia DATA SCIENTIST A data scientist is someone who is better at statistics than any software engineer and better at Software engineering than any statistician.” WHAT A DATA SCIENTIST DOES Most data scientists in the industry have advanced degrees and training in statistics, math, and computer science. Their experience is a vast horizon that also extends to data visualization, data mining, and information management. It is fairly common for them to have previous experience in infrastructure design, cloud computing, and data warehousing. SKILLS REQUIRED TO BECOME A DATA SCIENTIST Statistic and probability Algorithms Programming Languages (Java, Scala ,SQL, R, Phyton) Data mining Machine learning Who should go for this course? Fresher’s/Graduates Job Seekers Managers Data analysts Business analysts Operators End users Developers IT professionals Data science Course Duration and details Course Duration 90Days (3 months) Course Fees 27000Rs Only online training Note* Everyday session recordings are also available Venkat: 9059868766 Jio:7013158918 Email: [email protected] Address: Vlrtraining/Sivaitsoft PlotNo 126/b,2nd floor,Street Number 4, Addagutta Society, Jal Vayu Vihar,, Kukatpally, Hyderabad, Telangana 500085 Map Link https://goo.gl/maps/Nk9LziFjVXS2 Data science Course Content data science, data science and analytics, data science certification, data science course, data science degree, data science online, data science pdf,, data science skills, data science syllabus, data science tools, data scientist profile, data scientist skills, introduction to data science, learn data science, mathematics for data science, python data science, science data, scientific database, Download Pdf Data Science course content vlrtraining 9059868766 Hyderabad http://www.sivaitsoft.com/wp-content/uploads/2017/10/Data-Science-course-content-vlrtraining-9059868766-Hyderabad.pdf
Views: 26198 VLR Training
Import Data and Analyze with MATLAB
 
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Data are frequently available in text file format. This tutorial reviews how to import data, create trends and custom calculations, and then export the data in text file format from MATLAB. Source code is available from http://apmonitor.com/che263/uploads/Main/matlab_data_analysis.zip
Views: 397743 APMonitor.com
What is Big Data ? Introduction to BIG DATA: Types, Characteristics & Benefits - Technical knowledge
 
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Views: 29253 Study IQ education
Big Data Analytics | Tutorial​ #26 | DGIM algorithm ( Solved Problem)
 
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Suppose we have a window of length N on a binary stream. We want at all times to be able to answer queries of the form “how many 1’s are there in the last k bits?” for any k≤ N. For this purpose we use the DGIM algorithm. #RanjiRaj #BigData #DGIMNumerical Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj هذا الفيديو هو على سبيل المثال حلها من خوارزمية دجيم في البيانات الكبيرة Cette vidéo est sur l'exemple résolu de l'algorithme DGIM dans les grandes données Dieses Video ist auf dem gelösten Beispiel des DGIM-Algorithmus in großen Daten このビデオは、大きなデータのDGIMアルゴリズムの解決された例です Este video está en el ejemplo resuelto del algoritmo DGIM en grandes datos Это видео находится на решенном примере алгоритма DGIM в больших данных Add me on Facebook 👉 https://www.facebook.com/renji.nair.09 Follow on Twitter 👉 https://twitter.com/iamRanjiRaj Like TheStudyBeast on Facebook 👉 https://www.facebook.com/thestudybeast/ For more videos LIKE SHARE SUBSCRIBE
Views: 6454 Ranji Raj
Social Media Analytics Introduction
 
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Please view the full copyright statement at: http://public.dhe.ibm.com/software/data/sw-library/services/legalnotice.pdf
How Big Data Is Used In Amazon Recommendation Systems | Big Data Application & Example | Simplilearn
 
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This Big Data Video will help you understand how Amazon is using Big Data is ued in their recommendation syatems. You will understand the importance of Big Data using case study. Recommendation systems have impacted or even redefined our lives in many ways. One example of this impact is how our online shopping experience is being redefined. As we browse through products, the Recommendation system offer recommendations of products we might be interested in. Regardless of the perspectives, business or consumer, Recommendation systems have been immensely beneficial. And big data is the driving force behind Recommendation systems. Subscribe to Simplilearn channel for more Big Data and Hadoop Tutorials - https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Check our Big Data Training Video Playlist: https://www.youtube.com/playlist?list=PLEiEAq2VkUUJqp1k-g5W1mo37urJQOdCZ Big Data and Analytics Articles - https://www.simplilearn.com/resources/big-data-and-analytics?utm_campaign=Amazon-BigData-S4RL6prqtGQ&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Big Data and Hadoop, check our Big Data Hadoop and Spark Developer Certification Training Course: http://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training?utm_campaign=Amazon-BigData-S4RL6prqtGQ&utm_medium=Tutorials&utm_source=youtube #bigdata #bigdatatutorialforbeginners #bigdataanalytics #bigdatahadooptutorialforbeginners #bigdatacertification #HadoopTutorial - - - - - - - - - About Simplilearn's Big Data and Hadoop Certification Training Course: The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. Mastering real-time data processing using Spark: You will learn to do functional programming in Spark, implement Spark applications, understand parallel processing in Spark, and use Spark RDD optimization techniques. You will also learn the various interactive algorithm in Spark and use Spark SQL for creating, transforming, and querying data form. As a part of the course, you will be required to execute real-life industry-based projects using CloudLab. The projects included are in the domains of Banking, Telecommunication, Social media, Insurance, and E-commerce. This Big Data course also prepares you for the Cloudera CCA175 certification. - - - - - - - - What are the course objectives of this Big Data and Hadoop Certification Training Course? This course will enable you to: 1. Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames - - - - - - - - - - - Who should take up this Big Data and Hadoop Certification Training Course? Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology for the following professionals: 1. Software Developers and Architects 2. Analytics Professionals 3. Senior IT professionals 4. Testing and Mainframe professionals 5. Data Management Professionals 6. Business Intelligence Professionals 7. Project Managers 8. Aspiring Data Scientists - - - - - - - - For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 31856 Simplilearn
Convert PDF to Text in Hadoop/BigData
 
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Process complex data type in Hadoop. Convert millions of PDF files into text file in Hadoop Ecosystem.
Views: 1521 Vijay Garg
Data Analytics for Beginners | Introduction to Data Analytics | Data Analytics Tutorial
 
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Data Analytics for Beginners -Introduction to Data Analytics https://acadgild.com/big-data/data-analytics-training-certification?utm_campaign=enrol-data-analytics-beginners-THODdNXOjRw&utm_medium=VM&utm_source=youtube Hello and Welcome to data analytics tutorial conducted by ACADGILD. It’s an interactive online tutorial. Here are the topics covered in this training video: • Data Analysis and Interpretation • Why do I need an Analysis Plan? • Key components of a Data Analysis Plan • Analyzing and Interpreting Quantitative Data • Analyzing Survey Data • What is Business Analytics? • Application and Industry facts • Importance of Business analytics • Types of Analytics & examples • Data for Business Analytics • Understanding Data Types • Categorical Variables • Data Coding • Coding Systems • Coding, coding tip • Data Cleaning • Univariate Data Analysis • Statistics Describing a continuous variable distribution • Standard deviation • Distribution and percentiles • Analysis of categorical data • Observed Vs Expected Distribution • Identifying and solving business use cases • Recognizing, defining, structuring and analyzing the problem • Interpreting results and making the decision • Case Study Get started with Data Analytics with this tutorial. Happy Learning For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 270228 ACADGILD
Introduction to Datawarehouse in hindi | Data warehouse and data mining Lectures
 
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#datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 325632 Last moment tuitions
TLP / WA +62 813 – 8143 – 2012 Big Data Machine Learning Solution di Bekasi
 
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SARANA TERBAIK UNTUK UNTUK MEMPERMUDAH ANDA DALAM BERBISNIS !!!! Big data machine learning words, Big data machine learning solution, Big data machine learning tecniques, Big data machine learning training , Big data machine learning finance, Big data machine learning hadoop , Big data machine learning health care, Big data machine learning for disruption predictions, Big data machine learning finance , Big data machine learning ebook , Big data machine learning examples, Big data machine learning econometrics , Big data machine learning data mining , Big data machine learning data science, Big data machine learning definition , Big data machine learning difference, Big data machine learning diagram, Big data analytics mechine learning , Big data internasional, Big data Indonesia, Big data menurut para ahli , Big data technology , Big data machine learning cloud computing, Big data machine learning Colombia , Big data machine learning classification , Big data machine learning certification , Big data machine learning course, Big data machine learning consulting , Big data machine learning conference , Big data machine learning based secure health framework , Big data machine learning bussines intelligence , Big data machine learning and ai inportfolio management , Big data machine learning and graph analytics current state and future challenges , Big data machine learning and clinical medicine , Big data machine learning and the social sciences , Big data machine learning analytics , Big data machine learning datasets , Big data machine learning companies , Big data machine learning companies , Big data machine learning application , Big data machine learning python , Big data machine learning ppt , Big data machine learning architecture , Big data machine learning artifical intelligence , Big data machine learning ai , Big data machine learning tutorial , Big data machine learning pdf , Big data machine learning algorithmis , Big data menurut marr , Big data analysis pdf , Big data akuntasi , Big data pdf . “ BIG DATA DAN MACHINE LEARNING , SARANA TERBAIK UNTUK ANDA PARA PEMBISNIS , , ISI MATERI TERLENGKAP DAN MEMPERMUDAH ANDA DALAM HAL PEKERJAAN . “ Ingin perusahaan anda, bisnis anda, pekarjaan anda sukses sesuai yang anda inginkan , kini dizaman serba digital BIG DATA dan MACHINE LEARNING akan mempermudah anda dalam hal berbisninis. Selain itu, BIG DATA dan MACHINE LEARNING bermanfaat untuk anda para pembisnis sebagai : Memahami dan Menargetkan Pelanggan , Memahami dan Mengoptimalkan Proses Bisnis , Kuantifikasi Pribadi dan Optimalisasi Kinerja , Meningkatkan Kesehatan , Meningkatkan Performa Olahraga ,Meningkatkan Sains dan Penelitian , Mengoptimalkan Kinerja Mesin dan Alat Perangkat , Meningkatkan Keamanan dan Penegakan Hukum , Meningkatkan dan Mengoptimalkan Kota dan Negara , Perdagangan Keuangan . Jika anda atau para pembisnis ingin tahu lebih banyak tentang BIG DATA dan MACHINE LEARNING LEARNING . Info Selanjutnya bisa Hubungi kami : PT. Brilyan Trimatra Utama Jl.Dahlia Raya Blok E 12 Kota Bekasi Phone : (+62) 21 - 820 - 6565 Email: [email protected] TLP / WA : (+62) 813 – 8143 – 2012 Email : [email protected]
The beauty of data visualization - David McCandless
 
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View full lesson: http://ed.ted.com/lessons/david-mccandless-the-beauty-of-data-visualization David McCandless turns complex data sets, like worldwide military spending, media buzz, and Facebook status updates, into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world. Talk by David McCandless.
Views: 639196 TED-Ed
Regression Analysis | Data Science Tutorial | Simplilearn
 
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In statistical modeling, regression analysis is a statistical process for estimating the relationships among variables. It includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables (or 'predictors'). Data Science Certification Training - R Programming: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Regression-Data-Science-DtOYBxi4AIE&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse What are the course objectives? This course will enable you to: 1. Gain a foundational understanding of business analytics 2. Install R, R-studio, and workspace setup. You will also learn about the various R packages 3. Master the R programming and understand how various statements are executed in R 4. Gain an in-depth understanding of data structure used in R and learn to import/export data in R 5. Define, understand and use the various apply functions and DPLYP functions 6. Understand and use the various graphics in R for data visualization 7. Gain a basic understanding of the various statistical concepts 8. Understand and use hypothesis testing method to drive business decisions 9. Understand and use linear, non-linear regression models, and classification techniques for data analysis 10. Learn and use the various association rules and Apriori algorithm 11. Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: IT professionals looking for a career switch into data science and analytics Software developers looking for a career switch into data science and analytics Professionals working in data and business analytics Graduates looking to build a career in analytics and data science Anyone with a genuine interest in the data science field Experienced professionals who would like to harness data science in their fields Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 6513 Simplilearn
Video tutorial for crowdsourcing PDF data mining in Crowdcrafting
 
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This video shows how you can import from Dropbox PDF files into Crowdcrafting, to crowdsource the analysis of the PDF documents with just a few clicks.
Concept Drift Detector in Data Stream Mining
 
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Jorge Casillas, Shuo Wang, Xin Yao, Concept Drift Detection in Histogram-Based Straightforward Data Stream Classification, 6th International Workshop on Data Science and Big Data Analytics, IEEE International Conference on Data Mining, November 17-20, 2018 - Singapore http://decsai.ugr.es/~casillas/downloads/papers/casillas-ci44-icdm18.pdf This presentation shows a novel algorithm to accurately detect changes in non-stationary data streams in a very efficiently way. If you want to know how the yacare caiman, the cheetah and the racer snake are related to this research, do not stop watching the video! More videos here: http://decsai.ugr.es/~casillas/videos.html
Views: 220 Jorge Casillas
Big Data Analytics | Tutorial #27 | Page Rank Computation (Solved Problem)
 
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PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites. #RanjiRaj #BigData #PageRankNumerical Follow me on Instagram 👉 https://www.instagram.com/reng_army/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj يتعلق هذا الفيديو بحل مشكلة في ترتيب الصفحات في البيانات الكبيرة لحساب ترتيب الصفحات Cette vidéo consiste à résoudre un problème sur le classement des pages en grandes données pour calculer le rang des pages Dieses Video ist über das Lösen eines Problems auf Seitenrang in großen Daten, um den Rang der Seiten zu berechnen このビデオは、大きなデータのページランクに関する問題を解決し、ページのランクを計算することについてです Þetta myndband snýst um að leysa vandamál á síðuröðunar í stórum gögnum til að reikna stöðu síðurnar Это видео касается решения проблемы на ранжировании страницы в больших данных для вычисления ранга страниц Este video trata de resolver un problema en el rango de la página en grandes datos para calcular el rango de páginas Follow me on Twitter 👉 https://twitter.com/iamRanjiRaj Add me on Facebook 👉 https://www.facebook.com/renji.nair.09 Like TheStudyBeast on Facebook 👉 https://www.facebook.com/thestudybeast/ For more videos LIKE SHARE SUBSCRIBE
Views: 15859 Ranji Raj
TLP / WA +62 813 – 8143 – 2012 , Big data machine learning data mining
 
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SARANA TERBAIK UNTUK UNTUK MEMPERMUDAH ANDA DALAM BERBISNIS !!!! Big data machine learning words, Big data machine learning solution, Big data machine learning tecniques, Big data machine learning training , Big data machine learning finance, Big data machine learning hadoop , Big data machine learning health care, Big data machine learning for disruption predictions, Big data machine learning finance , Big data machine learning ebook , Big data machine learning examples, Big data machine learning econometrics , Big data machine learning data mining , Big data machine learning data science, Big data machine learning definition , Big data machine learning difference, Big data machine learning diagram, Big data analytics mechine learning , Big data internasional, Big data Indonesia, Big data menurut para ahli , Big data technology , Big data machine learning cloud computing, Big data machine learning Colombia , Big data machine learning classification , Big data machine learning certification , Big data machine learning course, Big data machine learning consulting , Big data machine learning conference , Big data machine learning based secure health framework , Big data machine learning bussines intelligence , Big data machine learning and ai inportfolio management , Big data machine learning and graph analytics current state and future challenges , Big data machine learning and clinical medicine , Big data machine learning and the social sciences , Big data machine learning analytics , Big data machine learning datasets , Big data machine learning companies , Big data machine learning companies , Big data machine learning application , Big data machine learning python , Big data machine learning ppt , Big data machine learning architecture , Big data machine learning artifical intelligence , Big data machine learning ai , Big data machine learning tutorial , Big data machine learning pdf , Big data machine learning algorithmis , Big data menurut marr , Big data analysis pdf , Big data akuntasi , Big data pdf . “ BIG DATA DAN MACHINE LEARNING , SARANA TERBAIK UNTUK ANDA PARA PEMBISNIS , , ISI MATERI TERLENGKAP DAN MEMPERMUDAH ANDA DALAM HAL PEKERJAAN . “ Ingin perusahaan anda, bisnis anda, pekarjaan anda sukses sesuai yang anda inginkan , kini dizaman serba digital BIG DATA dan MACHINE LEARNING akan mempermudah anda dalam hal berbisninis. Selain itu, BIG DATA dan MACHINE LEARNING bermanfaat untuk anda para pembisnis sebagai : Memahami dan Menargetkan Pelanggan , Memahami dan Mengoptimalkan Proses Bisnis , Kuantifikasi Pribadi dan Optimalisasi Kinerja , Meningkatkan Kesehatan , Meningkatkan Performa Olahraga ,Meningkatkan Sains dan Penelitian , Mengoptimalkan Kinerja Mesin dan Alat Perangkat , Meningkatkan Keamanan dan Penegakan Hukum , Meningkatkan dan Mengoptimalkan Kota dan Negara , Perdagangan Keuangan . Jika anda atau para pembisnis ingin tahu lebih banyak tentang BIG DATA dan MACHINE LEARNING Info Selanjutnya bisa Hubungi kami : PT. Brilyan Trimatra Utama Jl.Dahlia Raya Blok E 12 Kota Bekasi Phone : (+62) 21 - 820 - 6565 Email: [email protected] TLP / WA : (+62) 813 – 8143 – 2012 Email : [email protected]
Basic Data Analysis with Java : Business Intelligence | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2w2lQqE]. The aim of this video is to deal with Business Intelligence. It will use Apache POI for creating and reading spreadsheets, as well as show what users will do in MS Excel o Understand why as a data analyst, you need to save time using MS Excel o Perform some reads and writes of existing MS Excel spreadsheets For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 3010 Packt Video
Harness Oil and Gas Big  Keith Holdaway PDF
 
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Download : http://bit.ly/1ocKOwb Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models (Wiley and SAS Business Series) by Keith Holdaway pdf Description Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and rejuvenation of oil and gas assets. The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages
Views: 278 Lori Gonzales
How to Build a Text Mining, Machine Learning Document Classification System in R!
 
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We show how to build a machine learning document classification system from scratch in less than 30 minutes using R. We use a text mining approach to identify the speaker of unmarked presidential campaign speeches. Applications in brand management, auditing, fraud detection, electronic medical records, and more.
Views: 167195 Timothy DAuria
Implementing Big Data Analysis
 
04:28:37
Social Network for Developers ☞ https://morioh.com Aiodex’s Referral Program  will give you 20% -80% commission from their transaction fee for 7 years. The value will be calculated starting from the date the member you invite sign up ☞ https://aiodex.com/p/referral-program Next Generation Shorten Platform: Optimal choice to make a profit and analyze traffic sources on the network. Shorten URLs and Earn Big Money ☞ https://viralroll.com Get Free 15 Geek ☞ https://geekcash.org Developers Chat Channel ☞ https://discord.gg/KAe3AnN Playlists Video Tutorial ☞ http://dev.edupioneer.net/f086e182ab The Ultimate Hands-On Hadoop - Tame your Big Data! ☞ http://deal.codetrick.net/p/SJ0_BYGKZ Taming Big Data with Apache Spark and Python - Hands On! ☞ http://deal.codetrick.net/p/SkvnpBSXx Apache Spark 2.0 with Scala - Hands On with Big Data! ☞ http://deal.codetrick.net/p/B1MIbtMK- Scala and Spark for Big Data and Machine Learning ☞ http://deal.codetrick.net/p/SyeSqovQg Apache Spark with Scala - Learn Spark from a Big Data Guru ☞ http://deal.codetrick.net/p/rJfZjdrR- Spark and Python for Big Data with PySpark ☞ http://deal.codetrick.net/p/Sk-YpaVYyb Video source via: MVA ---------------------------------------------------- Website: https://goo.gl/XnM72d Website: https://goo.gl/AWpXfC Playlist: https://goo.gl/cknV8C Fanpage: https://goo.gl/kMBCFs Twitter: https://goo.gl/pNw922 Wordpress: https://goo.gl/qAJxMe Pinterest: https://goo.gl/GrRx7B Tumblr: https://goo.gl/6fTauh
Views: 408 Big Data Training
Bringing Order to Unstructured Data with R : Network Analysis of Tweets with R | packtpub.com
 
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This playlist/video has been uploaded for Marketing purposes and contains only selective videos. For the entire video course and code, visit [http://bit.ly/2xUR8T1]. This video covers steps for network analysis using tweets. • Show how to create term document matrix of tweets • Show how to develop network of terms using igraph package in R • Show how to create a network diagram For the latest Big Data and Business Intelligence video tutorials, please visit http://bit.ly/1HCjJik Find us on Facebook -- http://www.facebook.com/Packtvideo Follow us on Twitter - http://www.twitter.com/packtvideo
Views: 886 Packt Video
Lecture 6 - Trend Detection In Twitter Social Data (Analyzing Big Data With Twitter)
 
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http://blogs.ischool.berkeley.edu/i290-abdt-s12/ Lecture 6: Kostas Tsioutsiouliklis on Twitter Trends and how to compute them Lecture notes: http://blogs.ischool.berkeley.edu/i290-abdt-s12/files/2012/08/Kostas_Trends_Sept_13_2012.pdf Course: Information 290. Analyzing Big Data with Twitter School of Information UC Berkeley Prof. Marti Hearst Course description: How to store, process, analyze and make sense of Big Data is of increasing interest and importance to technology companies, a wide range of industries, and academic institutions. In this course, UC Berkeley professors and Twitter engineers will lecture on the most cutting-edge algorithms and software tools for data analytics as applied to Twitter microblog data. Topics will include applied natural language processing algorithms such as sentiment analysis, large scale anomaly detection, real-time search, information diffusion and outbreak detection, trend detection in social streams, recommendation algorithms, and advanced frameworks for distributed computing. Social science perspectives on analyzing social media will also be covered. This is a hands-on project course in which students are expected to form teams to complete intensive programming and analytics projects using the real-world example of Twitter data and code bases. Engineers from Twitter will help advise student projects, and students will have the option of presenting their final project presentations to an audience of engineers at the headquarters of Twitter in San Francisco (in addition to on campus). Project topics include building on existing infrastructure tools, building Twitter apps, and analyzing Twitter data. Access to data will be provided.
Medical Informatics Knowledge Management and Data Mining in Biomedicine Pdf
 
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Medical Informatics Knowledge Management and Data Mining in Biomedicine by Hsinchun Chen Pdf. Get Yours Now On http://medibookbank.com/search
Views: 13 Bertiza
Lecture: Mathematics of Big Data and Machine Learning
 
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MIT RES.LL-005 D4M: Signal Processing on Databases, Fall 2012 View the complete course: https://ocw.mit.edu/RESLL-005F12 Instructor: Jeremy Kepner Jeremy Kepner talked about his newly released book, "Mathematics of Big Data," which serves as the motivational material for the D4M course. License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
Views: 109171 MIT OpenCourseWare
MicroStrategy - Data Mining & Predictive Analytics - Online Training Video by MicroRooster
 
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Source: MicroRooster.blogspot.com Format: A MicroStrategy Online Training Video blog. Description: An introduction to Data Mining & Predictive Analytics using MicroStrategy. This demo explains how to use MicroStrategy for performing advanced data science analysis. Must have some understanding of basic data mining to take advantage of this entry level demo.
Views: 17213 MicroRooster
Mathematics of Machine Learning
 
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Do you need to know math to do machine learning? Yes! The big 4 math disciplines that make up machine learning are linear algebra, probability theory, calculus, and statistics. I'm going to cover how each are used by going through a linear regression problem that predicts the price of an apartment in NYC based on its price per square foot. Then we'll switch over to a logistic regression model to change it up a bit. This will be a hands-on way to see how each of these disciplines are used in the field. Code for this video (with coding challenge): https://github.com/llSourcell/math_of_machine_learning Please Subscribe! And like. And comment. That's what keeps me going. Want more education? Connect with me here: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology instagram: https://www.instagram.com/sirajraval Sign up for the next course at The School of AI: http://theschool.ai/ More learning resources: https://towardsdatascience.com/the-mathematics-of-machine-learning-894f046c568 https://ocw.mit.edu/courses/mathematics/18-657-mathematics-of-machine-learning-fall-2015/ https://www.quora.com/How-do-I-learn-mathematics-for-machine-learning https://courses.washington.edu/css490/2012.Winter/lecture_slides/02_math_essentials.pdf Join us in the Wizards Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Signup for my newsletter for exciting updates in the field of AI: https://goo.gl/FZzJ5w Hit the Join button above to sign up to become a member of my channel for access to exclusive content!
Views: 265822 Siraj Raval
K mean clustering algorithm with solve example
 
12:13
#kmean datawarehouse #datamining #lastmomenttuitions Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 434716 Last moment tuitions
Veri Madenciliği Nedir?
 
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Veri Madenciliği, Veri Madenciliği Dersleri, Veri Madenciliği Nedir?, Veri Madenciliği Eğitim Seti, Excel-Weka İlişkisi TAGS veri madenciliği yöntemleri, veri madenciliği nedir, microsoft excell, makro nedir, makrolarla excell dersleri, mining data, mining, datamining, what is data, data mining pdf, data mining techniques, data analysis, mineria, mineria de datos, data warehouse, data warehousing, database, data mining algorithm, data mining ppt, database mining, data mining software, big data, clustering, data mining tools, google data mining, classification, big data mining, smite, datamining smite, smite data mining, coursera, smite reddit, smite patch notes, smite wiki,0 gw2 data mining, big data analytics, bigdata, big data mining, big data, slideshare, kaggle, data scientist, hadoop,0 data mining meaning, jurnal data mining, python data mining, data mining adalah, nptel, python, data mining pdf TAGS http://kodkolik.net/
Data Structures and Algorithms Complete Tutorial Computer Education for All
 
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Computer Education for all provides complete lectures series on Data Structure and Applications which covers Introduction to Data Structure and its Types including all Steps involves in Data Structures:- Data Structure and algorithm Linear Data Structures and Non-Linear Data Structure on Stack Data Structure on Arrays Data Structure on Queue Data Structure on Linked List Data Structure on Tree Data Structure on Graphs Abstract Data Types Introduction to Algorithms Classifications of Algorithms Algorithm Analysis Algorithm Growth Function Array Operations Two dimensional Arrays Three Dimensional Arrays Multidimensional arrays Matrix operations Operations on linked lists Applications of linked lists Doubly linked lists Introductions to stacks Operations on stack Array based implementation of stack Queue Data Structures Operations on Queues Linked list based implementation of queues Application of Trees Binary Trees Types of Binary Trees Implementation of Binary Trees Binary Tree Traversal Preorder Post order In order Binary Search Tree Introduction to Sorting Analysis of Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Shell Sort Heap Sort Merge Sort Quick Sort Applications of Graphs Matrix representation of Graphs Implementations of Graphs Breadth First Search Topological Sorting Subscribe for More https://www.youtube.com/channel/UCiV37YIYars6msmIQXopIeQ Find us on Facebook: https://web.facebook.com/Computer-Education-for-All-1484033978567298 Java Programming Complete Tutorial for Beginners to Advance | Complete Java Training for all https://youtu.be/gg2PG3TwLx4
TLP / WA +62 813 – 8143 – 2012 , machine learning linear regression
 
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K Nearest Neighbor Algorithm (KNN) | Data Science | Big Data
 
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In this video you will learn about the KNN (K Nearest Neighbor Algorithm). KNN is a machine learning / data mining algorithm that is used for regression and classification purpose. This is a non parametric class of algorithms that works well with all kinds of data. The other types of data science algorithms that works similar to KNN are the Support vector machine, Logistic regression, Random forest, decision tree, Neural Network etc. ANalytics Study Pack : https://analyticuniversity.com Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 6935 Big Edu
Data Mining  Association Rule - Basic Concepts
 
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short introduction on Association Rule with definition & Example, are explained. Association rules are if/then statements used to find relationship between unrelated data in information repository or relational database. Parts of Association rule is explained with 2 measurements support and confidence. types of association rule such as single dimensional Association Rule,Multi dimensional Association rules and Hybrid Association rules are explained with Examples. Names of Association rule algorithm and fields where association rule is used is also mentioned.
Big Data Opportunity: Structured vs. Unstructured Data
 
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http://www.patrickschwerdtfeger.com/sbi/ Where's the opportunity in Big Data? Is it with structured data or unstructured data? Experts estimate that over 95% of the data in the world today is unstructured and only 5% is structured, so there's definitely a lot MORE unstructured data to be mined. The case histories so far suggest that the biggest opportunities lie in the messy unstructured data; the data the INCLUDES the outliers rather than marginalize them. The outliers add the most interesting insights to the process and allow the algorithms to calculate probabilities using the entire sample size, rather than relying on sampling inferences based on a small subset of the population. So research your unstructured data. Look at all those machine logs and metadata and see what insights you might be able to glean. Those are the building blocks for predictive analytics and algorithms that value.
Views: 16988 Patrick Schwerdtfeger
Association analysis: Frequent Patterns, Support, Confidence and Association Rules
 
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This lecture provides the introductory concepts of Frequent pattern mining in transnational databases.
Views: 65590 StudyKorner