Hands-On Machine Learning

By (author)Aurélien Géron
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Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you’ve learned. Programming experience is all you need to get started.


Use Scikit-learn to track an example ML project end to end
Explore several models, including support vector machines, decision trees, random forests, and ensemble methods
Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection
Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers
Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning


So, naturally you are excited about Machine Learning and would love to join the party! Perhaps you’d like to give your homemade robot a brain of its own? Make it recognize faces? Or learn to walk around? Or maybe your company has tons of data (user logs, financial data, production data, machine sensor data, hotline stats, HR reports, etc.), and more than likely you could unearth some hidden gems if you just knew where to look. With Machine Learning, you can accomplish the following & much more:

  • Segment customers and find the best marketing strategy for each group.
  • Recommend products for each client based on what similar clients bought.
  • Detect which transactions are likely to be fraudulent.
  • Forecast next year’s revenue.

Hands-On Machine Learning.





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