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Mastering Python for Finance

You're reading from   Mastering Python for Finance Implement advanced state-of-the-art financial statistical applications using Python

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Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789346466
Length 426 pages
Edition 2nd Edition
Languages
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Author (1):
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James Ma Weiming James Ma Weiming
Author Profile Icon James Ma Weiming
James Ma Weiming
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Getting Started with Python
2. Overview of Financial Analysis with Python FREE CHAPTER 3. Section 2: Financial Concepts
4. The Importance of Linearity in Finance 5. Nonlinearity in Finance 6. Numerical Methods for Pricing Options 7. Modeling Interest Rates and Derivatives 8. Statistical Analysis of Time Series Data 9. Section 3: A Hands-On Approach
10. Interactive Financial Analytics with the VIX 11. Building an Algorithmic Trading Platform 12. Implementing a Backtesting System 13. Machine Learning for Finance 14. Deep Learning for Finance 15. Other Books You May Enjoy

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Another popular deep learning Python library is Keras. In this section, we will use Keras to build a credit card payment default prediction model, and see how easy it is to construct an artificial neural network with five hidden layers, apply activation functions, and train this model as compared to TensorFlow.

Introduction to Keras

Keras is an open source deep learning library in Python, designed to be high level, user friendly, modular, and extensible. Keras was conceived to be an interface rather than a standalone machine learning framework, running on top of TensorFlow, CNTK, and Theano. Its huge community base with over 200,000 users makes it one of the most...

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