(Session 1: Spark Introduction Session 2: Spark2 Cluster Installation Session 3: SparkRDD Operation Session 4: SparkRDD Principle Analysis Session 5: Spark2Sql Import from MySQL Session 6: Spark1.6.2 SQL and MySQL Data Interaction Session 7: SparkSQLjava Operation MySQL Data Session 8: Spark Calculation of User's Preservation Conversion Rate Session 9: Spark Sorting User's Preservation and Order Conversion Rate Session 10: Getting User's Preservation and Order Conversion Rate Session 11: SparkP Ipeline Building Random Forest Regression Guess Model Session 12: Spark Random Forest Regression Guess Results and Store them in MySQL Session 13: Spark Compares the conversion rate of conservation to guess with the real conversion rate, and Decision Tree Model Construction Session 14: Spark Machine Learning Detailed introduction of various monitoring and non monitoring classification learning Session 15: Spark Collaborative Filtering Algorithm, Building a User and Product Model Session 16: End of Spark Collaborative Algorithm Recommending Products to Users Session 17: Mongodb Installation and Basic Operation Session 18: Combination of Spark and Mongodb Session 19: Spark Guessing Preservation and Storing Recommended Products to Users Session 20: Precautions for RDD Operation and Spark Memory Allocation Resource Tuning Session 21: Spark Comprehensive Learning Process and Summary
This document includes the following annexes:
_ rels\.rels
01.Spark Introduction.mp4
Learn More About Spark Machine Learning (User Behavior Analysis) (1). txt)
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