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Financial Data Science with Python An Integrated Approach to Analysis, Modeling,.epub
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用python分析建模的资料，内容非常精彩，600页的大型资料，实用，翔实，全部矢量文字适合投喂给大模型等工具，翻译也极为方便。
Chapter 1Introduction to Python Programming
Chapter 2Python Programming Fundamentals
Chapter 3Data Structures in Python
Chapter 4Objects and Classes in Python
Chapter 5NumPy for Financial Computation
Chapter 6Financial Data Processing With Pandas
Chapter 7Principle of Statistics for Financial Data Science
Chapter 8Financial Time Series Analysis
Chapter 9Data Visualization
Chapter 10Financial Modeling With OOP
Chapter 11Introduction to Machine Learning
Chapter 12Regression Machine Learning Models in Finance
Chapter 13Classification Machine Learning Models for Finance
Chapter 14Unsupervised Learning in Finance
Appendix
References
About the Author
Index
his text resource is designed for finance and business students with little background in Python and computer science, aiming to bridge the gap between current financial practices and data science applications.
In today’s data-driven world, the ability to analyze large data sets and extract meaningful insights is essential for financial professionals. Python has emerged as a powerful tool in this domain, offering extensive libraries and frameworks tailored for data analysis, financial modeling, and machine learning. This resource provides a comprehensive introduction to Python, starting from the basic Python programming and gradually advancing to more complex real-life applications. It aims to equip readers with a strong foundation in both Python programming and financial data science
Throughout this resource, we emphasize hands-on learning through practical examples and real-life projects. By working through these examples, readers will gain a deeper understanding of how to apply Python to solve common financial problems, perform data analysis, and build predictive models. Each chapter is designed to build on the previous ones, progressively introducing new concepts and techniques in a clear and structured manner.
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