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Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition by Eryk Lewinson [PDF EBOOK EPUB KINDLE]. Size: 57,399 KB. Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition Eryk Lewinson pdf.

[ BOOK PYTHON FOR FINANCE COOKBOOK: OVER 80 POWERFUL RECIPES FOR EFFECTIVE FINANCIAL DATA ANALYSIS, 2ND EDITION by ERYK LEWINSON OVERVIEW ]

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Use modern Python libraries such as pandas, NumPy, and scikit-learn and popular machine learning and deep learning methods to solve financial modeling problems

Purchase of the print or Kindle book includes a free eBook in the PDF format

Key Features

• Explore unique recipes for financial data processing and analysis with Python
  

• Apply classical and machine learning approaches to financial time series analysis
  

• Calculate
  

  
  

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  Book ID Asin: B09XDTFV7Q
  Book Title: Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition
  Book Author: Eryk Lewinson
  Book Format and Price:
  Book Format Name: Kindle
  Book Format Price: $29.99
  Book Format Name: Paperback
  Book Format Price: $49.99
  Book Price: $24.40
  Book Category: Kindle Store, Kindle eBooks, Computers & Technology and unknown
  Book Rating: 27 ratings
  
  Python for Finance Cookbook: Over 80 powerful recipes for effective financial data analysis, 2nd Edition by Eryk Lewinson Book Review
  
  Name: Gowtham Varma Bhupathiraju
  Rating: 4.0 out of 5 stars
  Title: .0 out of 5 stars An engaging and comprehensive guide to mastering financial data analysis with Python
  Date: Reviewed in the United States 🇺🇸 on May 29, 2023
  Review: The Python for Finance Cookbook offers readers a comprehensive introduction to the world of financial data analysis using Python. In addition to being well-structured, the book guides readers through logical progressions of topics from the very beginning. Throughout the book, each chapter is organized in such a manner that it is easy to follow along and comprehend what is being discussed.
  
  This book is incredibly helpful in that it breaks down scenarios into sections, beginning with "How to do it," followed by "How it works," and concluding with "There's more.". As a result of this format, readers can gain an understanding of Python techniques, their practical implementation, and additional options. Coding examples provided are clear and concise, making application to real-world financial problems easy.
  
  The author's explanations held my attention throughout the reading of the book. Each example presented a well-articulated thought process that guided me through the steps of the analysis and decision-making process. As a result of the author's clear language and the inclusion of practical tips, I was able to avoid common mistakes and gain a greater understanding of financial data analysis.
  
  Time series analysis, technical analysis, machine learning, and deep learning are all discussed in the book. In addition, Streamlit is introduced, which is a valuable tool for developing interactive web applications for presenting analysis results. An important aspect of the course was the emphasis on exploratory data analysis, which allowed me to uncover insights and draw meaningful conclusions from the financial information.
  
  As a whole, I found the "Python for Finance Cookbook" to be an extremely helpful resource. In this book, you will learn how to analyze financial data using Python to enhance your skills as a financial analyst, data scientist, or Python developer. My proficiency in using Python for financial data analysis has significantly improved as a result of its well-structured outline, detailed explanations, and thought-provoking examples provided in this book. To anyone seeking a deeper understanding of this field, I strongly recommend this book.
  
  Name: Steven Fernandes
  Rating: 5.0 out of 5 stars
  Title: .0 out of 5 stars A must-read guide to process and analyze financial data
  Date: Reviewed in the United States 🇺🇸 on May 22, 2023
  Review: "Financial Data Analysis with Python" is a must-read guide that efficiently uses Python libraries to process and analyze financial data. This new edition emphasizes exploratory data analysis, making data visualization more intuitive. Moreover, it introduces Streamlit, a tool for developing interactive web applications to display technical analysis results.
  The book is a trove of actionable instructions that boosts proficiency in financial data analysis for both personal and professional endeavors. It also wisely preempts potential issues, offering practical solutions. Briefly put, this book is a comprehensive and practical resource for anyone aiming to master Python in financial data analysis.
  
  Name: Om S
  Rating: 5.0 out of 5 stars
  Title: .0 out of 5 stars Explore Classical and Modern Approaches to Financial Data Analysis and Processing
  Date: Reviewed in the United States 🇺🇸 on March 17, 2023
  Review: The Python for Finance Cookbook is an excellent resource for financial analysts, data analysts and scientists, and Python developers who want to master financial data analysis using Python. The book provides a comprehensive overview of classical and modern approaches to financial data analysis and processing, including time series analysis, technical analysis, machine learning-based approaches, and deep learning.
  
  The book is well-structured, with clear explanations of the concepts, and includes practical examples and code snippets that enable readers to implement the techniques described in the book. The authors have also included tips on avoiding common mistakes and pitfalls, which is particularly helpful for those new to financial data analysis.
  
  One of the strengths of the book is its emphasis on exploratory data analysis, which enables readers to better understand financial data and draw meaningful conclusions from it. The use of Streamlit to create elegant, interactive web applications to present the results of technical analyses is also a useful feature of the book.
  
  Overall, the Python for Finance Cookbook is an excellent resource for anyone who wants to master financial data analysis using Python. The book is comprehensive, well-structured, and includes practical examples that enable readers to apply the techniques described in the book to real-world problems. I highly recommend this book to anyone who wants to become proficient in financial data analysis.
  
  Name: Isaac D. Tucker-Rasbury
  Rating: 4.0 out of 5 stars
  Title: .0 out of 5 stars A Solid Resource with Detailed Explanations
  Date: Reviewed in the United States 🇺🇸 on December 30, 2022
  Review: I love how the book takes the task of teaching Python 🐍 and breaks it into super digestible and easily practiced pieces. That’s hard to do! That makes this book a great resource for anyone willing to trek through the details.
  
  I wouldn’t put this book in the hands of newbie though without some conversation though. I think they might miss the forest for the trees with this. The problem though is that a lot of analytics is self taught, so I’d say that I’d put this in the hands of someone who is a little further down their journey - maybe one project under their belt and can easily set up a practice environment - and looking to go deeper!
  
  Super solid resource though and one that I’m definitely going to enjoy digging into