The case is king, mainly based on actual combat, and an omni-directional analysis of the top ten cases based on spark2.x machine learning.

Course download address: https://pan.baidu.com/s/1LuffQVoVjJjDkN3jT2TfQA extraction Code: ytyc

This course mainly explains that Spark MLlib,Spark MLlib is an efficient, fast and scalable distributed computing framework, and implements commonly used machine learning, such as clustering, classification, regression and other algorithms. This lesson refuses boring narration, and will start with the basic knowledge of Spark and matrix vector step by step, then thoroughly explain the theory of each algorithm, show the implementation of Spark source code in detail, and finally analyze the actual combat through examples to help you really master Spark MLlib distributed machine learning from theory to practice.

Omni-directional analysis of the top ten cases:

Case 1. Construction of classification system for StumbleUpon dataset based on Kaggle

Case 2. Building a regression model based on BikeSharing data sets

Case 3. News classification based on NewsCorpora dataset text processing

Case 4. Network traffic detection model based on KMeans

Case 5. Build CRT prediction model based on Kaggle Avazu advertising dataset.

Case 6. Taxi track analysis based on clustering KMeans

Case 7. Prediction of forest vegetation based on decision tree

Case 8. Prediction of forest vegetation based on DataFrame API ML

Case 9. Music recommendation based on Audioscrobbler dataset

Case 10. Movie recommendation based on MovieLens dataset