Building Machine Learning Systems with Python - Third Edition
by Luis Pedro Coelho, Willi Richert, Matthieu Brucher
What this book covers
Chapter 1, Getting Started with Python Machine Learning, introduces the basic idea of machine learning and TensorFlow with a very simple example. Despite its simplicity, it will challenge us with the risk of overfitting.
Chapter 2, Classifying with Real-world Examples, uses real data to explore classification by training a computer to be able to distinguish between different classes of flowers.
Chapter 3, Regression, explains how to use regression to handle data, a classic topic that is still relevant today. You will also learn about advanced regression techniques such as Lasso and ElasticNet.
Chapter 4, Classification I – Detecting Poor Answers, demonstrates how to use the bias-variance trade-off to debug machine learning ...
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