This repository contains the source code and accompanying materials for the book "Machine Learning and Deep Learning with Python" by James Chen. This book is a comprehensive guide to understanding and implementing machine learning and deep learning techniques with Python.
Title: Machine Learning and Deep Learning with Python
Subtitle: Use Python Jupyter to Implement Mathematical Concepts, Machine Learning Algorithms and Deep Learning Neural Networks
Author: James Chen (LinkedIn: linkedin.com/in/jchen8000)
Available at:
ISBN: 978-1-7389084-2-4 (eBook), Amazon Kindle, Apple Books, Google Play Books, Rakuten Kobo
ISBN: 978-1-7389084-0-0 (Paperback), Amazon
ISBN: 978-1-7389084-1-7 (Hardcover), Amazon
Written with both beginners and experienced developers in mind, this book provides a thorough overview of the foundations of machine learning and deep learning, including mathematical fundamentals, optimization algorithms, and neural networks. Starting with the basics of Python programming, this book gradually builds up to more advanced topics, such as artificial neural networks, convolutional neural networks, and generative adversarial networks. Each chapter is filled with clear explanations, practical examples, and step-by-step tutorials that allow readers to gain a deep understanding of the underlying principles of machine learning and deep learning.
Throughout the book, readers will also learn how to use popular Python libraries and packages, including numpy, pandas, scikit-learn, TensorFlow, and Keras, to build and train powerful machine learning and deep learning models for a variety of real-world applications, such as regression and classification, K-means, support vector machines, and recommender systems.
Whether you are a seasoned data scientist or a beginner looking to enter the world of machine learning, this book is the ultimate resource for mastering these cutting-edge technologies and taking your skills to the next level. High-school level of mathematical knowledge and all levels (including entry-level) of programming skills are good to start, all Python codes are available at Github.com.
The source codes are organized in the folders corresponding to the the chapters of the book.
Open the desired code file in Google Colab or your preferred Jupyter environment.
Refer to the book for guidance on using the code examples.
docker pull jchen8000/tf_gpu_jupyterlab:latest
The contents of this repository are licensed under GPL-3.0 License. See the LICENSE file for more details.
If you have any questions or suggestions regarding the book or the repository, please feel free to reach out to the author at linkedin.com/in/jchen8000.