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TORRENT DETAILS

[FreeCoursesOnline.Me] [Packt] Big Data Analytics Projects With Apache Spark [FCO]

TORRENT SUMMARY

	Status:	All the torrents in this section have been verified by our verification system
Category:	Other
Infohash	48d400f0b81f499b572d8135e249d56a24ba1596
Size:	634.5 MB in 27 files
Release Date(s):	Torrent Release: 29-03-2019 by user
Swarm:	0 Seeds & 0 Peers
Vote:	No votes yet.

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/.

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FILE LIST

Filename		Size
	1.Finding Top Selling Product/01.The Course Overview.mp4	21.4 MB
	1.Finding Top Selling Product/02.Explaining Ways of Joining Datasets.mp4	73.3 MB
	1.Finding Top Selling Product/03.Developing Spark Algorithm for Joining_Windowing Datasets.mp4	40 MB
	1.Finding Top Selling Product/04.Testing Logic in MapReduce Spark — Finding Top Sellers.mp4	14.3 MB
	1.Finding Top Selling Product/05.Drawing Conclusions from Top Sellers Data.mp4	24.3 MB
	2.Market Basket Analysis/06.Market Basket Analysis Goals.mp4	36.7 MB
	2.Market Basket Analysis/07.Where MBA Algorithms Are Useful.mp4	32.6 MB
	2.Market Basket Analysis/08.Implementing MBA MapReduce Algorithm in Spark.mp4	28.9 MB
	2.Market Basket Analysis/09.Finding Association Rules Between Products.mp4	24.5 MB
	3.Finding an Author Using Probabilistic Logistic Regression/10.Analyzing Post for an Author.mp4	9.5 MB
	3.Finding an Author Using Probabilistic Logistic Regression/11.Extracting Information from Unstructured Text.mp4	16.5 MB
	3.Finding an Author Using Probabilistic Logistic Regression/12.Extracting Information via Spark DataFrame.mp4	19.3 MB
	3.Finding an Author Using Probabilistic Logistic Regression/13.Sentiment Analysis of Posts Using Logistic Regression.mp4	19.4 MB
	3.Finding an Author Using Probabilistic Logistic Regression/14.Finding an Author of a Post.mp4	10.8 MB
	4.Content-Based Recommendation System - Movies/15.Content-Based Recommendation Systems Explanation.mp4	11 MB
	4.Content-Based Recommendation System - Movies/16.Finding Correlation Between Movies and Users.mp4	15.8 MB
	4.Content-Based Recommendation System - Movies/17.Testing Logic in MapReduce Spark.mp4	28.6 MB
	4.Content-Based Recommendation System - Movies/18.Finding Recommendation for Given User.mp4	19.6 MB
	5.Social Network Friend Recommendation/19.Finding Common Friends Problem — Graph Approach.mp4	7.4 MB
	5.Social Network Friend Recommendation/20.Creating a Graph Using GraphX and Property Graph.mp4	35 MB
	5.Social Network Friend Recommendation/21.Solution — Examining Available Methods.mp4	25.3 MB
	5.Social Network Friend Recommendation/22.Finding Closest Friend for Given User Using Page Rank.mp4	118 MB
	Discuss.FTUForum.com.html	31.9 KB
	Exercise Files/code_33899.zip	2 MB
	FreeCoursesOnline.Me.html	108.3 KB
	FTUForum.com.html	100.4 KB
	How you can help Team-FTU.txt	235 B

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