Python Machine Learning - Second Edition

Python Machine Learning - Second EditionMachine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschkas bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine

Machine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschkas bestselling book, Python Machine Learning. Thoroughly updated using the latest Python open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis."margin-top: 0.6em; margin-bottom: 1.2em; padding: 0px; color: rgb(73, 73, 73); font-family: Ubuntu, sans-serif; background-color: rgb(243, 247, 248);"Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow deep learning library. The scikit-learn code has also been fully updated to include recent improvements and additions to this versatile machine learning library."margin-top: 0.6em; margin-bottom: 1.2em; padding: 0px; color: rgb(73, 73, 73); font-family: Ubuntu, sans-serif; background-color: rgb(243, 247, 248);"Sebastian Raschka and Vahid Mirjalilis unique insight and expertise introduce you to machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. the end of the book, youll be ready to meet the new data analysis opportunities in todays world.If youve read the first edition of this book, youll be delighted to find a new balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. Youll 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.