This is the code repository for Big Data Analytics Projects with Apache Spark [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.
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.
- 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.
To fully benefit from the coverage included in this course, you will need:
- Basic understanding of Scala
- Basic understanding of Spark
This course has the following software requirements:
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Knowlege in data analysis
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Knowledge of Hadoop and Apache Spark to perform efficient Big Data analytics