Cover
Title Page
Copyright and Credits
Packt Upsell
Contributors
Table of Contents
Preface
Chapter 1: Building Your Own Prediction Models
Classification overview and evaluation techniques
Evaluation
Decision trees
Common APIs for scikit-learn classifiers
Prediction involving decision trees and student performance data
Summary
Chapter 2: Prediction with Random Forests
Random forests
Usage of random forest
Predicting bird species with random forests
Making a confusion matrix for the data
Summary
Chapter 3: Applications for Comment Classification
Text classification
Machine learning techniques
Bag of words
Detecting YouTube comment spam
Word2Vec models
Doc2Vec
Document vector
Detecting positive or negative sentiments in user reviews
Summary
Chapter 4: Neural Networks
Understanding neural networks
Feed-forward neural networks
Identifying the genre of a song with neural networks
Revising the spam detector to use neural networks
Summary
Chapter 5: Deep Learning
Deep learning methods
Convolutions and pooling
Identifying handwritten mathematical symbols with CNNs
Revisiting the bird species identifier to use images
Summary
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Index