Szczegóły ebooka

Machine Learning for Finance. Principles and practice for financial insiders

Machine Learning for Finance. Principles and practice for financial insiders

Jannes Klaas

Ebook
Machine Learning for Finance explores new advances in machine learning and shows how they can be applied across the financial sector, including insurance, transactions, and lending. This book explains the concepts and algorithms behind the main machine learning techniques and provides example Python code for implementing the models yourself.

The book is based on Jannes Klaas’ experience of running machine learning training courses for financial professionals. Rather than providing ready-made financial algorithms, the book focuses on advanced machine learning concepts and ideas that can be applied in a wide variety of ways.

The book systematically explains how machine learning works on structured data, text, images, and time series. You'll cover generative adversarial learning, reinforcement learning, debugging, and launching machine learning products. Later chapters will discuss how to fight bias in machine learning. The book ends with an exploration of Bayesian inference and probabilistic programming.
  • 1. Neural Networks and Gradient-Based Optimization
  • 2. Applying Machine Learning to Structured Data
  • 3. Utilizing Computer Vision
  • 4. Understanding Time Series
  • 5. Parsing Textual Data with Natural Language Processing
  • 6. Using Generative Models
  • 7. Reinforcement Learning for Financial Markets
  • 8. Privacy, Debugging, and Launching Your Products
  • 9. Fighting Bias
  • 10. Bayesian Inference and Probabilistic Programming
  • Tytuł: Machine Learning for Finance. Principles and practice for financial insiders
  • Autor: Jannes Klaas
  • Tytuł oryginału: Machine Learning for Finance. Principles and practice for financial insiders
  • ISBN: 9781789134698, 9781789134698
  • Data wydania: 2019-05-30
  • Format: Ebook
  • Identyfikator pozycji: e_2avc
  • Wydawca: Packt Publishing