Название: Build Your Own AI Investor: With Machine Learning and Python, Step by Step, 2nd EditionАвтор: Damon Lee
Издательство: valueinvestingai.com
Год: 2021
Страниц: 281
Язык: английский
Формат: pdf, epub
Размер: 37.2 MB
This Second Edition improves clarity of code, general formatting, text explanations as well as updating the AI for 2021 stock selection.
Build Your Own AI Investor:
- Breaks down Value Investing for the AI revolution, whilst being accessible to anyone, even if you've never invested in stocks or coded before
- Teaches Python step-by-step, from installation and the basics, all the way to creating your own AI Investor that picks stocks for you
- Watch the AI Portfolio: See AI portfolio performance over time on the website, made with the code in this book.
AI Investing
Not sure how to approach the stock investing with AI?
No time to learn these programming skills? Think it sounds daunting?
Think the investing game is rigged by computer-wielding financial wizards?
Do It All Yourself
Discover Value Investing, the approach taken by the best investors: Warren Buffett, Joel Greenblatt, Michael Burry, Peter Lynch, John Templeton, Charlie Munger
Build your own AI! Have your own Value Investing machine provide stock picks for the year
No time? Set up the AI in a weekend by skipping ahead to Chapter 5
Anyone can learn the computing tools, every step is in this book to build a value investing AI
The Machine Learning algorithms are all well and good, but we will need to do some programming to use them. To someone who has never done any coding before this might sound daunting, though there is no reason to worry because the programming language we will be using is Python. Python has effectively become the Machine Learning lingua franca.
For beginners, exercises are provided in every chapter to develop your Python skills, slowly building competence until you can use Machine Learning tools for general problems.
For advanced readers this books provides a good basis in value investing, framing the stock selection problem in a quantitative way, using Machine Learning algorithms on stock market data.
Who Should Read This Book:
Besides people who just want to make the investing AI, there are others whom this book will be useful:
People learning to code with Python will find a book that holds your hand from Python installation and setup all the way to creating a working AI stock picker.
Those who have some programming experience, but want to understand Machine Learning algorithms will find tutorials to teach the concepts required, with a final hands-on application at the end that is useful.
Programmers with no investing knowledge will get an understanding of the stock market approached from a data perspective with good theoretical backing, in doing so understanding why there is more to a stock than a ticker symbol that goes up and down. It will provide perspective on how the investing problem should be approached, and how Machine Learning can be applied in a theoretically consistent manner.
Stock investors who want to know what Machine Learning and Python tools can do for them, will find that the coding knowledge will enable them to make far more interesting screens than what online services offer as well as gaining Machine Learning knowledge that can be used to inform investing decisions in as many ways as they have the creativity to imagine.
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