--- product_id: 221915022 title: "Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python" price: "₹ 8648" currency: INR in_stock: true reviews_count: 13 url: https://www.desertcart.in/products/221915022-machine-learning-for-algorithmic-trading-predictive-models-to-extract-signals store_origin: IN region: India --- # Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python **Price:** ₹ 8648 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python - **How much does it cost?** ₹ 8648 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.in](https://www.desertcart.in/products/221915022-machine-learning-for-algorithmic-trading-predictive-models-to-extract-signals) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python [Stefan Jansen] on desertcart.com. *FREE* shipping on qualifying offers. Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python Review: Built My First Successful Trading Bot - As someone who's been interested in both machine learning and financial markets, I was looking for a comprehensive resource that would bridge these two worlds. Stefan Jansen's "Machine Learning for Algorithmic Trading" not only delivered on this promise but exceeded my expectations by enabling me to build my own profitable algorithmic trading bot. What sets this book apart is how it provides a complete end-to-end workflow. The progression from basic concepts to advanced implementation is logical and thorough. Jansen starts with essential market data handling, moves through feature engineering techniques, and culminates in sophisticated model development and backtesting. The Python code examples using popular libraries like pandas, scikit-learn, and PyTorch provided immediate practical value rather than just theoretical concepts. I particularly appreciated the diverse range of ML techniques covered - from traditional algorithms to deep learning approaches. The sections on feature engineering and alpha factor research were especially valuable for my trading bot development. The book doesn't just teach you algorithms; it shows you how to apply them meaningfully to extract signals from market data. The inclusion of backtrader and Zipline for strategy testing was instrumental in helping me validate my ideas before risking real capital. I was able to iterate on my strategies, identify weaknesses, and refine my approach using the framework provided in the book. While the book is certainly dense at 800+ pages, it serves as both a learning resource and a reference manual. I continue to revisit specific chapters as I enhance my trading strategies. Even with some prior knowledge in both programming and finance, I found tremendous value in Jansen's comprehensive approach. One small caveat: some of the code examples require updating as libraries evolve, but the core concepts remain solid and adaptable. In fact, working through these updates enhanced my understanding of the underlying systems. Bottom line - this book delivered exactly what I needed: the knowledge and tools to transform my interest in ML and markets into a functioning algorithmic trading system. For anyone serious about applying machine learning to trading, this book is an essential investment that can potentially pay for itself many times over. Review: Great book, nice examples. - The book overall is very didactic, my only recommendation would be to use a more simple set up as many of the recommended tools and libraries are outdated, not the author’s fault but renders impossible to follow some of the examples. A more simple set of standard libraries, perhaps could be more stable and allow to follow better the presented examples. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | #59,203 in Books ( See Top 100 in Books ) #3 in Financial Engineering (Books) #11 in Machine Theory (Books) #33 in Python Programming | | Customer Reviews | 4.4 4.4 out of 5 stars (411) | | Dimensions | 7.5 x 1.86 x 9.25 inches | | Edition | 2nd ed. | | ISBN-10 | 1839217715 | | ISBN-13 | 978-1839217715 | | Item Weight | 3.24 pounds | | Language | English | | Print length | 820 pages | | Publication date | July 31, 2020 | | Publisher | Packt Publishing | ## Images ![Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python - Image 1](https://m.media-amazon.com/images/I/71ycxzrff0L.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ Built My First Successful Trading Bot *by R***L on March 31, 2025* As someone who's been interested in both machine learning and financial markets, I was looking for a comprehensive resource that would bridge these two worlds. Stefan Jansen's "Machine Learning for Algorithmic Trading" not only delivered on this promise but exceeded my expectations by enabling me to build my own profitable algorithmic trading bot. What sets this book apart is how it provides a complete end-to-end workflow. The progression from basic concepts to advanced implementation is logical and thorough. Jansen starts with essential market data handling, moves through feature engineering techniques, and culminates in sophisticated model development and backtesting. The Python code examples using popular libraries like pandas, scikit-learn, and PyTorch provided immediate practical value rather than just theoretical concepts. I particularly appreciated the diverse range of ML techniques covered - from traditional algorithms to deep learning approaches. The sections on feature engineering and alpha factor research were especially valuable for my trading bot development. The book doesn't just teach you algorithms; it shows you how to apply them meaningfully to extract signals from market data. The inclusion of backtrader and Zipline for strategy testing was instrumental in helping me validate my ideas before risking real capital. I was able to iterate on my strategies, identify weaknesses, and refine my approach using the framework provided in the book. While the book is certainly dense at 800+ pages, it serves as both a learning resource and a reference manual. I continue to revisit specific chapters as I enhance my trading strategies. Even with some prior knowledge in both programming and finance, I found tremendous value in Jansen's comprehensive approach. One small caveat: some of the code examples require updating as libraries evolve, but the core concepts remain solid and adaptable. In fact, working through these updates enhanced my understanding of the underlying systems. Bottom line - this book delivered exactly what I needed: the knowledge and tools to transform my interest in ML and markets into a functioning algorithmic trading system. For anyone serious about applying machine learning to trading, this book is an essential investment that can potentially pay for itself many times over. ### ⭐⭐⭐⭐⭐ Great book, nice examples. *by S***R on July 30, 2024* The book overall is very didactic, my only recommendation would be to use a more simple set up as many of the recommended tools and libraries are outdated, not the author’s fault but renders impossible to follow some of the examples. A more simple set of standard libraries, perhaps could be more stable and allow to follow better the presented examples. ### ⭐⭐⭐⭐ A good book with improvement scopes *by R***) on December 28, 2024* A promising book with plenty of room for improvement. While there are some noticeable typos, the overall reading experience is enjoyable. A more refined and updated version, perhaps a third edition, would enhance its appeal significantly. ## Frequently Bought Together - Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition - Python for Algorithmic Trading Cookbook: Recipes for designing, building, and deploying algorithmic trading strategies with Python - Quantitative Trading: How to Build Your Own Algorithmic Trading Business (Wiley Trading) --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.in/products/221915022-machine-learning-for-algorithmic-trading-predictive-models-to-extract-signals](https://www.desertcart.in/products/221915022-machine-learning-for-algorithmic-trading-predictive-models-to-extract-signals) --- *Product available on Desertcart India* *Store origin: IN* *Last updated: 2026-04-30*