Book Image

Machine Learning for Finance

By : Jannes Klaas
Book Image

Machine Learning for Finance

By: Jannes Klaas

Overview of this book

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.
Table of Contents (15 chapters)
Machine Learning for Finance
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Further reading

You made it to the end of the book! What are you going to do now? Read more books! Machine learning, and in particular, deep learning, is a fast-moving field, so any reading list risks being outdated by the time you read it. However, the following list aims to show you the most relevant books that have a safety net of remaining relevant over the coming years.

General data analysis

Wes McKinney, Python for Data Analysis,

Wes is the original creator of pandas, a popular Python data-handling tool that we saw in Chapter 2, Applying Machine Learning to Structured Data. pandas is a core component of any data science workflow in Python and will remain so for the foreseeable future. Investing in sound knowledge of the tools he presents is definitely worth your time.

Sound science in machine learning

Marcos Lopez de Prado, Advances in Financial Machine Learning,