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Machine learning is eating the software world. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka's bestselling book, Python Machine Learning. Modernized and extended to include the latest open source technologies, including scikit-learn, Keras, and TensorFlow, Python Machine Learning Second Edition offers the practical knowledge and techniques you need to create effective machine learning and deep learning applications in Python. Sebastian Raschka and Vahid Mirjalili's unique insight and expertise introduce you to machine learning and deep learning algorithms, before progressing to advanced topics in data analysis. This book combines the theoretical principles of machine learning with a hands-on coding approach for a thorough grasp of machine learning theory and implementation using Python.
|DATE DE PUBLICATION||2017-Sep-15|
|TAILLE DU FICHIER||10,45 MB|
|NOM DE FICHIER||Python Machine Learning.pdf|
Learn Applied Machine Learning in Python from University of Michigan. This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will ...
Machine Learning for Beginners: An Introduction to Neural Networks — one more good simple explanation of how Neural Networks work and how to implement one from scratch in Python. Step 2. Learn the Basics of Python Syntax. Great news: you do not need a full learning course, as Python and data analysis are not synonymous.