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Python Machine Learning - Second Edition by Sebastian Raschka & Vahid Mirjalili

The first edition of this book, is a balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. You’ll be able to learn and work with TensorFlow more deeply than ever before, and get essential coverage of the Keras neural network library, along with the most recent updates to scikit-learn.

The second edition of Python Machine Learning opens the doors for developers and data scientists who want a practical approach to machine learning and deep learning. In this thoroughly updated edition, you’ll explore the machine learning process using Python and the latest open source technologies, including scikit-learn and TensorFlow. It is ideal for developers and data scientists who want to teach computers how to learn from data.

 

Key features:

  • A practical approach to key frameworks in data science, machine learning, and deep learning
  • Use the most powerful Python libraries to implement machine learning and deep learning
  • Get to know the best practices to improve and optimize your machine learning systems and algorithms

You can read a preview of the book here.

About the Authors

Sebastian Raschka

Sebastian Raschka, author of the bestselling book, Python Machine Learning, has many years of experience with coding in Python. His work and contributions have recently been recognized by the departmental outstanding graduate student award 2016-2017, as well as the ACM Computing Reviews' Best of 2016 award.

Vahid Mirjalili

Vahid Mirjalili obtained his PhD in mechanical engineering working on novel methods for large-scale, computational simulations of molecular structures. Vahid picked Python as his number-one choice of programming language, and throughout his academic and research career he has gained tremendous experience with coding in Python.

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