Machine Learning for Finance: Principles and practice for financial insiders

Machine Learning for Finance: Principles and practice for financial insiders

English | May 31st, 2019 | ISBN: 1789136369 | 456 Pages | EPUB (True/Retail Copy) | 20.68 MB

Plan and build useful machine learning systems for financial services, with full working Python code

Key Features
Build machine learning systems that will be useful across the financial services industry
Discover how machine learning can solve finance industry challenges
Gain the machine learning insights and skills fintech companies value most

Book Description
Machine learning skills are essential for anybody working in financial data analysis. Machine Learning for Finance shows you how to build machine learning models for use in financial services organizations. It shows you how to work with all the key machine learning models, from simple regression to advanced neural networks.

You will see how to use machine learning to automate manual tasks, identify and address systemic bias, and find new insights and patterns hidden in available data. Machine Learning for Finance encourages and equips you to find new ways to use data to serve an organization's business goals.

Broad in scope yet deeply practical in approach, Machine Learning for Finance will help you to apply machine learning in all parts of a financial organization's infrastructure. If you work or plan to work in fintech, and want to gain one of the most valuable skills in the sector today, this book is for you.

What you will learn
Practical machine learning for the finance sector
Build machine learning systems that support the goals of financial organizations
Think creatively about problems and how machine learning can solve them
Identify and reduce sources of bias from machine learning models
Apply machine learning to structured data, natural language, photographs, and written text related to finance
Use machine learning to detect fraud, forecast financial trends, analyze customer sentiments, and more
Implement heuristic baselines, time series, generative models, and reinforcement learning in Python, scikit-learn, Keras, and TensorFlow

Who this book is for
Machine Learning for Finance is for financial professionals who want to develop and apply machine learning skills, and for students entering the field. You should be comfortable with Python and the basic data science stack, such as NumPy, pandas, and Matplotlib, to get the most out of this book.


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