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Description

In Part III of this series, we cover the fundamentals of machine learning, focusing on:

  • validation methodology (reprint)
  • nearest neighbor, k-means, support vector machines, principal component analysis
  • tree-based methods: decision trees, bagging, random forest, boosting, XGBoost
  • artificial neural networks and deep learning
  • reinforcement learning

The focus is on algorithmic development and programming. We code each technique from scratch in Python, using an object-oriented approach.



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Product Details

  • Apr 29, 2022 Pub Date:
  • 9781941043134 ISBN-13:
  • 1941043135 ISBN-10:
  • 316.0 pages Paperback
  • English Language