Plan and build useful machine learning systems for financial services, with full working Python code Key Features Build
1,597 296 21MB
English Pages xiv, 435 pages: illustrations; 24 cm Year 2018;2019
Table of contents :
Neural networks and gradient-based optimization --
Applying machine learning to structured data --
Utilizing computer vision --
Understanding time series --
Parsing textual data with natural language processing --
Using generative models --
Reinforcement learning for financial markets --
Privacy, debugging, and launching your products --
Fighting bias --
Bayesian inference and probabilistic programming.