{"product_id":"applied-machine-learning-a-practical-guide-to-preparing-data-selecting-algorithms-and-implementing-machine-learning-models-in-the-real-world-rheinwerk-computing","title":"Applied Machine Learning: Using Machine Learning to Solve Business Problems","description":"\u003cp\u003eA machine learning model is only as useful as the business question behind it. Jason Hodson builds this practical guide around three use cases, taking each from raw data to a deployed prediction.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eReadical Key Points\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003eFirst edition, paperback, 440 pages, published 2026 by Rheinwerk Computing\u003c\/li\u003e\n\u003cli\u003eThree worked use cases, each built on a separate dataset: a retail case, customer retention and crime predictions\u003c\/li\u003e\n\u003cli\u003eCovers data exploration and cleaning, regression, decision trees, random forests, gradient boosting, clustering, validation metrics and interpretability\u003c\/li\u003e\n\u003cli\u003eSetup chapters use GitHub and Anaconda; sample code is available for download\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003eHodson moves through the full life of a model. Readers set up their tools, explore and clean the data, and choose an approach with a decision framework that favors the simplest model that works. Later chapters test results with validation metrics and k-fold cross-validation, explain what a model is doing, iterate on it, then put it into production, monitor it and measure its business impact.\u003c\/p\u003e\n\u003cp\u003eThe book serves analysts, data professionals and technically minded managers who need machine learning to answer a real business question. Because the three use cases return at every stage, a reader can follow one project from first look at the data to a monitored model. A closing chapter covers learning with generative AI. No book can supply a team's own data; what this one supplies is a repeatable path for working with it.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbout the Author\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003eJason Hodson's career has centered on data roles for close to a decade, including forecasting work built on applied machine learning, and he has mentored colleagues in analytics and programming. He taught himself before completing a master's in business analytics.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e Brand New and Readical Ready.\u003c\/p\u003e\n\u003cp\u003eReadical™ is an independent bookstore and reading-products brand built around a simple idea: books matter most when what we learn leaves the page and enters our lives.\u003c\/p\u003e\n\u003cp\u003e\u003cb\u003eApply the Page. Get Readical™.\u003c\/b\u003e\u003c\/p\u003e","brand":"Rheinwerk Computing","offers":[{"title":"Default Title","offer_id":48025452740757,"sku":"NEW-ING-1493227580","price":59.95,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0800\/5861\/3909\/files\/upload-1789784695894.jpg?v=1789784697","url":"https:\/\/readical.com\/products\/applied-machine-learning-a-practical-guide-to-preparing-data-selecting-algorithms-and-implementing-machine-learning-models-in-the-real-world-rheinwerk-computing","provider":"Readical","version":"1.0","type":"link"}