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Showing 5 outstanding Python books published on
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Applied Machine Learning and AI for Engineers: Solve Business Problems That Can't Be Solved Algorithmically

by Jeff Prosise

Applied Machine Learning and AI for Engineers provides examples and illustrations from the AI and ML course Prosise teaches at companies and research institutions worldwide. There's no fluff and no scary equations—just a fast start for engineers and software developers, complete with hands-on examples.
Published on : Dec. 20, 2022
Python version: TH
425 pages

Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis

by Eryk Lewinson

In this new edition of the Python for Finance Cookbook, you will explore classical quantitative finance approaches to data modeling, such as GARCH, CAPM, factor models, as well as modern machine learning and deep learning solutions.You will use popular Python libraries that, in a few lines of code, provide the means to quickly process, analyze, and draw conclusions from financial data. In this new edition, more emphasis was put on exploratory data analysis to help you visualize and better understand financial data.
Published on : Dec. 30, 2022
Python version: TH
740 pages

Functional Python Programming: Use a functional approach to write succinct, expressive, and efficient Python code,

by Steven F. Lott

Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with examples centered around data cleaning and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage
Published on : Dec. 30, 2022
Python version: TH
576 pages

Introduction to Financial Derivatives with Python

by Elisa Alòs

Introduction to Financial Derivatives with Python is an ideal textbook for an undergraduate course on derivatives, whether on a finance, economics, or financial mathematics programme. As well as covering all of the essential topics one would expect to be covered, the book also includes the basis of the numerical techniques most used in the financial industry, and their implementation in Python.
Published on : Dec. 15, 2022
Python version: TH
252 pages

Pandas for Everyone: Python Data Analysis

by Daniel Chen

Pandas for Everyone, brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world data science problems such as using regularization to prevent data overfitting, or when to use unsupervised machine learning methods to find the underlying structure in a data set.
Published on : Dec. 30, 2022
Python version: TH
512 pages