Szczegóły ebooka

Statistics for Machine Learning. Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Statistics for Machine Learning. Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Pratap Dangeti

Ebook
Complex statistics in machine learning worry a lot of developers. Knowing statistics helps you build strong machine learning models that are optimized for a given problem statement.

This book will teach you all it takes to perform the complex statistical computations that are required for machine learning. You will gain information on the statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. You will see real-world examples that discuss the statistical side of machine learning and familiarize yourself with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more.

By the end of the book, you will have mastered the statistics required for machine learning and will be able to apply your new skills to any sort of industry problem.
  • 1. Journey from Statistics to Machine Learning
  • 2. Parallelism of Statistics and Machine Learning
  • 3. Logistic Regression vs. Random Forest
  • 4. Tree-Based Machine Learning models
  • 5. K-Nearest Neighbors & Naïve Bayes
  • 6. Support Vector Machines & Neural Networks
  • 7. Recommendation Engines
  • 8. Unsupervised Learning
  • 9. Reinforcement Learning
  • Tytuł: Statistics for Machine Learning. Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
  • Autor: Pratap Dangeti
  • Tytuł oryginału: Statistics for Machine Learning. Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R
  • ISBN: 9781788291224, 9781788291224
  • Data wydania: 2017-07-21
  • Format: Ebook
  • Identyfikator pozycji: e_15mj
  • Wydawca: Packt Publishing