Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 [3rd Edition | Retail] 1789955750, 978-1789955750
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforceme
3,261 726 22MB
English Pages 770 Year 12 Dec 2019
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Table of contents :
01. Giving Computers the Ability to Learn from Data
02. Training Simple ML Algorithms for Classification
03. ML Classifiers Using scikit-learn
04. Building Good Training Datasets - Data Preprocessing
05. Compressing Data via Dimensionality Reduction
06. Best Practices for Model Evaluation and Hyperparameter Tuning
07. Combining Different Models for Ensemble Learning
08. Applying ML to Sentiment Analysis
09. Embedding a ML Model into a Web Application
10. Predicting Continuous Target Variables with Regression Analysis
11. Working with Unlabeled Data - Clustering Analysis
12. Implementing Multilayer Artificial Neural Networks
13. Parallelizing Neural Network Training with TensorFlow
14. TensorFlow Mechanics
15. Classifying Images with Deep Convolutional Neural Networks
16. Modeling Sequential Data Using Recurrent Neural Networks
17. GANs for Synthesizing New Data
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