Discover the powerful Apache Spark platform for machine learning. Learn about preprocessing data, applying algorithms to a variety of machine learning problems, and more.
Overview
Syllabus
Introduction
- Welcome
- Introduction to Spark
- Steps in the machine learning process
- Install Spark
- Organizing data in DataFrames
- Components of Spark MLlib
- Introduction to preprocessing
- Normalize numeric data
- Standardize numeric data
- Bucketize numeric data
- Tokenize text data
- TF-IDF
- Summary of preprocessing
- Introduction to clustering
- K-means clustering
- Hierarchical clustering
- Summary of clustering techniques
- Introduction to classification
- Preprocessing the Iris data set
- Naive Bayes classification
- Multilayer perceptron classification
- Decision trees classification
- Summary of classification algorithms
- Introduction to regresssion
- Preprocessing regression data
- Linear regression
- Decision tree regression
- Gradient-boosted tree regression
- Summary of regression algorithms
- Understand recommendation systems
- Collaborative filtering
- Tips for using Spark MLlib
Taught by
Dan Sullivan
