Spark for Machine Learning & AI

Discover the powerful Apache Spark platform for machine learning. Learn about preprocessing data, applying algorithms to a variety of machine learning problems, and more.

Syllabus

Introduction

Welcome

1. Introduction to Spark and MLlib

Introduction to Spark
Steps in the machine learning process
Install Spark
Organizing data in DataFrames
Components of Spark MLlib

2. Data Preparation and Transformation

Introduction to preprocessing
Normalize numeric data
Standardize numeric data
Bucketize numeric data
Tokenize text data
TF-IDF
Summary of preprocessing

3. Clustering

Introduction to clustering
K-means clustering
Hierarchical clustering
Summary of clustering techniques

4. Classification

Introduction to classification
Preprocessing the Iris data set
Naive Bayes classification
Multilayer perceptron classification
Decision trees classification
Summary of classification algorithms

5. Regression

Introduction to regresssion
Preprocessing regression data
Linear regression
Decision tree regression
Gradient-boosted tree regression
Summary of regression algorithms

6. Recommendations

Understand recommendation systems
Collaborative filtering

Conclusion

Tips for using Spark MLlib

Taught by

Dan Sullivan

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