Hands-on ML with Scikit-Learn, Keras & TF by Aurelien Geron

• This Books assumes you know close to nothing about machine learning.
• We will be using production-ready Python frameworks
  • Scikit-Learn
  • Keras
  • TensorFlow
• This book favors a hands-on approach through a series of working examples and just a little bit of theory.
• Prerequesites
  • Some Python programming experience
  • Familiarity with NumPy, Pandas, and Matplotlib
  • A reasonable understanding of college-level math (calculus, probability, Linear Algebra, and statistics)
• The first part of the book is mostly based on Scikit-Learn, while the 2nd part is using Keras/TensorFlow.

Roadmap

1. The Fundamentals of Machine Learning

• The Machine Learning Landscape
• End-to-End Machine Learning Project
• Classification
• Training Models
• Support Vector Machines
• Decision Trees
• Ensemble Learning and Random Forests
• Dimensionality Reduction
• Unsupervised Learning Techniques

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