Big Data Analytics Projects with Apache Spark [Video]
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.
|Course Length||2 hours 4 minutes|
|Date Of Publication||24 Jun 2018|
|Explaining Ways of Joining Datasets|
|Developing Spark Algorithm for Joining/Windowing Datasets|
|Testing Logic in MapReduce Spark — Finding Top Sellers|
|Drawing Conclusions from Top Sellers Data|
|Creating a Graph Using GraphX and Property Graph|
|Solution — Examining Available Methods|
|Finding Closest Friend for Given User Using Page Rank|