Machine Learning with Spark > PACKT 원서리스트

1: Getting Up and Running with Spark
Installing and setting up Spark locally
Spark clusters
The Spark programming model
The first step to a Spark program in Scala
The first step to a Spark program in Java
The first step to a Spark program in Python
Getting Spark running on Amazon EC2
Summary

2: Designing a Machine Learning System
Introducing MovieStream
Business use cases for a machine learning system
Types of machine learning models
The components of a data-driven machine learning system
An architecture for a machine learning system
Summary

3: Obtaining, Processing, and Preparing Data with Spark
Accessing publicly available datasets
Exploring and visualizing your data
Processing and transforming your data
Extracting useful features from your data
Summary

4: Building a Recommendation Engine with Spark
Types of recommendation models
Extracting the right features from your data
Training the recommendation model
Using the recommendation model
Evaluating the performance of recommendation models
Summary

5: Building a Classification Model with Spark
Types of classification models
Extracting the right features from your data
Training classification models
Using classification models
Evaluating the performance of classification models
Improving model performance and tuning parameters
Summary

6: Building a Regression Model with Spark
Types of regression models
Extracting the right features from your data
Training and using regression models
Evaluating the performance of regression models
Improving model performance and tuning parameters
Summary

7: Building a Clustering Model with Spark
Types of clustering models
Extracting the right features from your data
Training a clustering model
Making predictions using a clustering model
Evaluating the performance of clustering models
Tuning parameters for clustering models
Summary

8: Dimensionality Reduction with Spark
Types of dimensionality reduction
Extracting the right features from your data
Training a dimensionality reduction model
Using a dimensionality reduction model
Evaluating dimensionality reduction models
Summary

9: Advanced Text Processing with Spark
What's so special about text data?
Extracting the right features from your data
Using a TF-IDF model
Evaluating the impact of text processing
Word2Vec models
Summary

10: Real-time Machine Learning with Spark Streaming
Online learning
Stream processing
Creating a Spark Streaming application
Online learning with Spark Streaming
Online model evaluation
Summary

Appendix A: Index