Financial Data Science with Python
eBook - ePub

Financial Data Science with Python

An Integrated Approach to Analysis, Modeling, and Machine Learning

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Financial Data Science with Python

An Integrated Approach to Analysis, Modeling, and Machine Learning

About this book

In today's finance industry, data-driven decision-making is essential. Financial Data Science with Python: An Integrated Approach to Analysis, Modeling, and Machine Learning bridges the gap between traditional finance and modern data science, offering a comprehensive guide for students, analysts, and professionals.

This book equips readers with the tools to analyze complex financial data, build predictive models, and apply machine learning techniques to real-world financial challenges.

Beginning with foundational Python concepts, the author covers essential topics like data structures, object-oriented programming, and key libraries such as NumPy and Pandas. The book advances into more complex areas, including financial data processing, time series analysis with ARIMA and GARCH models, and both supervised and unsupervised machine learning methods tailored to finance. Practical techniques like regression, classification, and clustering are explored in a financial context.

A key feature is the hands-on approach. Through real-world examples, projects, and exercises, readers will apply Python to tasks like risk assessment, market forecasting, and financial pattern recognition. All code examples are provided in Jupyter Notebooks, enhancing interactivity.

Whether you're a student building foundational skills, a financial analyst enhancing technical expertise, or a professional staying competitive in a data-driven industry, this book offers the knowledge and tools to succeed in financial data science.

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Yes, you can access Financial Data Science with Python by Haojun Chen in PDF and/or ePUB format, as well as other popular books in Business & Financial Engineering. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Front Cover
  2. Half Title
  3. Title Page
  4. Copyright
  5. Description
  6. Contents
  7. Preface
  8. Guide for Readers
  9. Chapter 1 Introduction to Python Programming
  10. Chapter 2 Python Programming Fundamentals
  11. Chapter 3 Data Structures in Python
  12. Chapter 4 Objects and Classes in Python
  13. Chapter 5 NumPy for Financial Computation
  14. Chapter 6 Financial Data Processing With Pandas
  15. Chapter 7 Principle of Statistics for Financial Data Science
  16. Chapter 8 Financial Time Series Analysis
  17. Chapter 9 Data Visualization
  18. Chapter 10 Financial Modeling With OOP
  19. Chapter 11 Introduction to Machine Learning
  20. Chapter 12 Regression Machine Learning Models in Finance
  21. Chapter 13 Classification Machine Learning Models for Finance
  22. Chapter 14 Unsupervised Learning in Finance
  23. Appendix
  24. References
  25. About the Author
  26. Index
  27. Back Cover