Python 3 for Machine Learning
Oswald Campesato
Feb 2020 · Mercury Learning and Information
Ebook
364
Pages
About this ebook
This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2.
Features:
Features:
- Provides the reader with basic Python 3 programming concepts related to machine learning
- Includes separate appendices for regular expressions, Keras, and TensorFlow 2
About the author
Oswald Campesato specializes in Deep Learning, Python, Data Science, and generative AI. He is the author/co-author of over forty-five books including Google Gemini for Python, Large Language Models, and GPT-4 for Developers (all Mercury Learning).
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