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You're reading from Python Machine Learning, Second Edition Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow

Product type Paperback

Published in Sep 2017

Publisher Packt

ISBN-13 9781787125933

Length 622 pages

Edition 2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Deep Learning

Authors (4):

Sebastian Raschka

Vahid Mirjalili

Jared Huffman

Ryan Sun

Preface

1. Giving Computers the Ability to Learn from Data FREE CHAPTER

2. Training Simple Machine Learning Algorithms for Classification

3. A Tour of Machine Learning Classifiers Using scikit-learn

4. Building Good Training Sets – Data Preprocessing

5. Compressing Data via Dimensionality Reduction

6. Learning Best Practices for Model Evaluation and Hyperparameter Tuning

7. Combining Different Models for Ensemble Learning

8. Applying Machine Learning to Sentiment Analysis

9. Embedding a Machine Learning Model into a Web Application

10. Predicting Continuous Target Variables with Regression Analysis

11. Working with Unlabeled Data – Clustering Analysis

12. Implementing a Multilayer Artificial Neural Network from Scratch

13. Parallelizing Neural Network Training with TensorFlow

14. Going Deeper – The Mechanics of TensorFlow

15. Classifying Images with Deep Convolutional Neural Networks

16. Modeling Sequential Data Using Recurrent Neural Networks

Index

accuracy / Optimizing the precision and recall of a classification model
activation functions
- selecting, for multilayer networks / Choosing activation functions for multilayer networks
activations
- computing, in RNN / Computing activations in an RNN
AdaBoost
- applying, scikit-learn used / Applying AdaBoost using scikit-learn
AdaBoost (Adaptive Boosting)
- weak learners, leveraging via / Leveraging weak learners via adaptive boosting
Adaline
- implementing, in Python / Implementing Adaline in Python
/ First steps with scikit-learn – training a perceptron
Adaline implementation
- converting, into algotithm for logistic regression / Converting an Adaline implementation into an algorithm for logistic regression
ADAptive Linear NEuron (Adaline) / Solving regression for regression parameters with gradient descent
ADAptive LInear NEuron (Adaline) / Adaptive linear neurons and the convergence of learning...