Teach Machine Learning using the only interactive solution with integrated Jupyter Notebooks Machine Learning is the first complete, interactive introduction to the foundational algorithms and techniques for machine learning using Python. Balances computational skills with conceptual and practical machine learning...
Building Machine Learning Systems with Python(2013): Master the art of machine learning with Python and build effective machine learning systems with this intensive hands-on guide. Learning scikit-learn: Machine Learning in Python(2013): Experience the benefits of machine learning techniques by applyin...
Hands-On Machine Learning with scikit:learn and Scientific Python Toolkits上QQ阅读APP,阅读体验更流畅 领看书特权 Summary 上QQ阅读看本书,第一时间看更新 登录订阅本章 > Other Books You May Enjoy 上QQ阅读看本书,第一时间看更新 登录订阅本章 >...
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurélien Géron Python machine learning practitioners will love this book.Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlowis a great resource to get...
2) Building Machine Learning Systems with Python - Willi Richert, Luis Pedro Coelho This book goes into significant detail on how to use scikit-learn for regression and classification tasks. In addition to extensive coverage on scikit-learn it actually considers other libraries such as gensim (for...
Learn the Iris dataset, find out how to build complex classifiers, and get to grips with clustering through practical examples that deliver complex ideas with clarity. Dig deeper into machine learning, and discover guidance on classification and regression, with practical machine learning projects ...
Hands-On Ensemble Learning with Python, 2019. Ensemble Machine Learning Cookbook, 2019. Did I miss a book on ensemble learning? Let me know in the comments below. Have you read any of these books on ensemble learning? What did you think? Let me know in the comments. ...
This fundamental book on Artificial Neural Networks has its emphasis on clear concepts, ease of understanding and simple examples. Written for undergraduate students, the book presents a large variety of standard neural networks with architecture, algori