Building Machine Learning Systems with Python - Third Edition

This comprehensive guide introduces you to building intelligent machine learning systems with Python. By covering the use of libraries such as scikit-learn and TensorFlow, you will learn to implement both classical and cutting-edge machine learning techniques effectively. A strong focus on practical examples and real-world challenges ensures you'll gain actionable skills.

What this Book will help me do

• Implement supervised and unsupervised learning algorithms, enhancing your analytic capabilities.
• Develop neural networks with TensorFlow to understand deep learning applications.
• Use regression and classification to solve common prediction and categorization problems.
• Master techniques for handling real-world data and preparing it for machine learning pipelines.
• Deploy and fine-tune machine learning models in Python for production-grade applications.

Author(s)

The authors, Pedro Coelho, Willi Richert, and Brucher, are professionals with extensive experience in programming, artificial intelligence, and data science. They have combined their knowledge to provide a clear and practical introduction to machine learning systems, emphasizing hands-on learning and application.

Who is it for?

This book is perfect for Python developers, data scientists, and aspiring machine learning practitioners ready to take on intermediate to advanced projects. A fundamental understanding of Python is recommended to fully benefit from the material. If you are eager to deploy machine learning solutions or explore AI, this book is your guide.