--- product_id: 101488008 title: "The Hundred-Page Machine Learning Book" price: "£43.72" currency: GBP in_stock: true reviews_count: 13 url: https://www.desertcart.co.uk/products/101488008-the-hundred-page-machine-learning-book store_origin: GB region: Great Britain --- # The Hundred-Page Machine Learning Book **Price:** £43.72 **Availability:** ✅ In Stock ## Quick Answers - **What is this?** The Hundred-Page Machine Learning Book - **How much does it cost?** £43.72 with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.co.uk](https://www.desertcart.co.uk/products/101488008-the-hundred-page-machine-learning-book) ## 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 Discover the essentials of machine learning in a compact 100-page guide, praised by leading experts for its practical insights and comprehensive coverage. Review: I admire what the author achieved here - The advantage of short books like this is that if they are well written the author has to think carefully about what to write and how to write it. That's certainly been done here. After a crash course in what ML is and some mathematical notation, a few popular ML algorithms are introduced, before Burkov takes a look at what a learning algorithm fundamentally does: optimising a particular function (normally by minimising a loss function). Other parts of the book go into ML practice, deep learning, practical problems and solutions, and tips and tricks for situations you might run into (e.g. handling multiple outputs). Unsupervised learning, word embeddings and ranking and recommendation systems are discussed. The book's conclusion talks about other areas to learn about which weren't present. The book is dense in parts, no doubt about it. Burkov lays down all the mathematical formulae but also explains things pretty well and touches on the intuition behind key ideas, along with useful pictures and diagrams. That is one of the things I liked the most: it is rigorous, concise, but not unclear. Another thing I really liked is that it touches on very practical problem discussed less frequently elsewhere (e.g. imbalanced datasets) and interesting approaches you won't find in more traditional resources (like one and zero shot learning). In contrast to what some other reviewers on the back of book say, I'd say that this book is probably not the best one for absolute beginners. It would be much more useful when you know what ML is and have done a project or two, at least. To sum up, if you want an information packed ML book that has both theory and useful practical tips, read this. Review: Learn the background behind the methods - This is not the book you get for sample code and immediate applications, but it is a fantastic resource to learn more of the theory behind machine learning methods. You will improve your use of models by learning the background in this book. ## Technical Specifications | Specification | Value | |---------------|-------| | Best Sellers Rank | 28,307 in Books ( See Top 100 in Books ) 12 in Computer Information Systems 791 in Popular Mathematics | | Customer reviews | 4.6 4.6 out of 5 stars (1,239) | | Dimensions | 19.05 x 0.97 x 23.5 cm | | ISBN-10 | 199957950X | | ISBN-13 | 978-1999579500 | | Item weight | 378 g | | Language | English | | Part of series | The Hundred-Page Books | | Print length | 160 pages | | Publication date | 13 Jan. 2019 | | Publisher | Andriy Burkov | ## Images ![The Hundred-Page Machine Learning Book - Image 1](https://m.media-amazon.com/images/I/51DQ9Bs-h-L.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ I admire what the author achieved here *by H***. on 27 October 2023* The advantage of short books like this is that if they are well written the author has to think carefully about what to write and how to write it. That's certainly been done here. After a crash course in what ML is and some mathematical notation, a few popular ML algorithms are introduced, before Burkov takes a look at what a learning algorithm fundamentally does: optimising a particular function (normally by minimising a loss function). Other parts of the book go into ML practice, deep learning, practical problems and solutions, and tips and tricks for situations you might run into (e.g. handling multiple outputs). Unsupervised learning, word embeddings and ranking and recommendation systems are discussed. The book's conclusion talks about other areas to learn about which weren't present. The book is dense in parts, no doubt about it. Burkov lays down all the mathematical formulae but also explains things pretty well and touches on the intuition behind key ideas, along with useful pictures and diagrams. That is one of the things I liked the most: it is rigorous, concise, but not unclear. Another thing I really liked is that it touches on very practical problem discussed less frequently elsewhere (e.g. imbalanced datasets) and interesting approaches you won't find in more traditional resources (like one and zero shot learning). In contrast to what some other reviewers on the back of book say, I'd say that this book is probably not the best one for absolute beginners. It would be much more useful when you know what ML is and have done a project or two, at least. To sum up, if you want an information packed ML book that has both theory and useful practical tips, read this. ### ⭐⭐⭐⭐⭐ Learn the background behind the methods *by C***T on 11 May 2025* This is not the book you get for sample code and immediate applications, but it is a fantastic resource to learn more of the theory behind machine learning methods. You will improve your use of models by learning the background in this book. ### ⭐⭐⭐⭐ too expensive but has some essential parts *by J***O on 29 December 2019* This books price is a shame. Aside from that the content is good for the most part. Sadly it doesnt explain back propagation which would have been nice and theres no gaussian section which seemed odd. The best part about this book for me is its one of the few that actually explains the notation properly. I find that this subject appears a lot more difficult because of the dense notation which many books go out of their way not to define. This one does a good job of making sure you understand what all the letters and subscripts mean, and for that I was very happy ## Frequently Bought Together - The Hundred-Page Machine Learning Book - Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems - Machine Learning Engineering --- ## 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.co.uk/products/101488008-the-hundred-page-machine-learning-book](https://www.desertcart.co.uk/products/101488008-the-hundred-page-machine-learning-book) --- *Product available on Desertcart Great Britain* *Store origin: GB* *Last updated: 2026-04-24*