Name: | [Packt] Big Data Analytics Projects with Apache Spark [FCO] GloDLS |
Description: By: Tomasz Lelek Released: Monday, June 25, 2018 Torrent Contains: 29 Files, 6 Folders Course Source: https://www.packtpub.com/big-data-and-business-intelligence/big-data-analytics-projects-apache-spark-video Perform real-life data operations with Apache Spark. Video Details ISBN 9781789132373 Course Length 2 hour 4 minutes Table of Contents • FINDING TOP SELLING PRODUCT • MARKET BASKET ANALYSIS • FINDING AN AUTHOR USING PROBABILISTIC LOGISTIC REGRESSION • CONTENT-BASED RECOMMENDATION SYSTEM: MOVIES • SOCIAL NETWORK FRIEND RECOMMENDATION Video Description Ready to use statistical and machine-learning techniques across large data sets? This course shows you how the Apache Spark and the Hadoop MapReduce ecosystem is perfect for the job. This course contains various projects that consist of real-world examples. The first project is to find top selling products for an e-commerce business by efficiently joining data sets in the Map/Reduce paradigm. Next, a Market Basket Analysis will help you identify items likely to be purchased together and find correlations between items in a set of transactions. Moving on, you'll learn about probabilistic logistic regression by finding an author for a post. Next, you'll build a content-based recommendation system for movies to predict whether an action will happen, which we’ll do by building a trained model. Finally, we’ll use the Map/Reduce Spark program to calculate mutual friends on social network. By the end of this course, you’ll have been exposed to a wide variety of mathematical techniques that can be utilized as training models with the Spark and Hadoop software, and know how to solve common problems. Style and Approach This will help you perform data analysis, introducing to each subject by example and practice that makes the audience more productive after each video. What You Will Learn • Learn See how to process big data effectively • Examine a number of real-world use cases and hands-on code examples. • Build Hadoop and Apache Spark jobs that process data quickly and effectively. • Write programs for complex data analysis and solving to solve real real-world problems • Explore the Map/Reduce Hadoop and Spark approach for solvinto solveg data analysis problems. Authors Tomasz Lelek Tomasz Lelek is a Software Engineer, programming mostly in Java, Scala. He has worked with ML algorithms for the past 5 years, with production experience in processing petabytes of data. He is passionate about nearly everything associated with software development and believes that we should always try to consider different solutions and approaches before solving a problem. Recently he was a speaker at conferences in Poland, Confitura and JDD (Java Developers Day), and also at Krakow Scala User Group. He has also conducted a live coding session at Geecon Conference. He is a co-founder of www.initlearn.com, an e-learning platform that was built with the Java language. He has also written articles about everything related to the Java world: http://www.baeldung.com/. | |
YouTube Video: | |
Category: | Tutorials |
Language: | English |
Total Size: | 634.53 MB |
Info Hash: | 48D400F0B81F499B572D8135E249D56A24BA1596 |
Added By: | Prom3th3uS |
Date Added: | 2019-03-29 13:41:28 |
Torrent Status: | Torrent Verified |
Ratings: | Not Yet Rated (Log in to rate it) |
URL | Seeders | Leechers | Completed |
---|---|---|---|
https://tracker.fastdownload.xyz:443/announce | 0 | 0 | 0 |
udp://tracker.torrent.eu.org:451/announce | 3 | 2 | 23 |
udp://tracker.cyberia.is:6969/announce | 0 | 0 | 0 |
udp://tracker.leechers-paradise.org:6969/announce | 0 | 0 | 0 |
udp://open.stealth.si:80/announce | 3 | 2 | 189 |
udp://tracker.coppersurfer.tk:6969/announce | 0 | 0 | 0 |
udp://tracker.cyberia.is:6969/announce | 0 | 0 | 0 |
https://opentracker.xyz:443/announce | 0 | 0 | 0 |
https://t.quic.ws:443/announce | 0 | 0 | 0 |
udp://9.rarbg.to:2710/announce | 0 | 0 | 0 |
udp://tracker.opentrackr.org:1337/announce | 3 | 2 | 13 |
udp://ipv4.tracker.harry.lu:80/announce | 1 | 1 | 0 |
udp://tracker.coppersurfer.tk:6969/announce | 0 | 0 | 0 |
udp://tracker.internetwarriors.net:1337/announce | 0 | 0 | 0 |
udp://open.demonii.si:1337/announce | 0 | 0 | 0 |