{"product_id":"designing-machine-learning-systems","title":"Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications by Chip Huyen","description":"\u003ch2\u003eDesigning Machine Learning Systems: An Iterative Process for Production-Ready Applications by Chip Huyen\u003c\/h2\u003e\n\u003cp data-path-to-node=\"6\"\u003eThe core thesis of \u003ci data-path-to-node=\"6\" data-index-in-node=\"19\"\u003eDesigning Machine Learning Systems\u003c\/i\u003e is that deploying a model is the easy part—maintaining it in production while user behaviors actively shift is the real engineering challenge. Traditional software development handles static, deterministic logic. Machine learning, however, is deeply non-deterministic and entirely dependent on live data flows. Huyen introduces a holistic, end-to-end framework that views ML engineering as an iterative loop spanning data engineering, model development, deployment, infrastructure scaling, and continuous real-time monitoring.\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\"\u003e\u003cspan class=\"text-block-with-attachment\"\u003e\u003cspan class=\"attachment-container search-images\"\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\"\u003e\u003cspan class=\"text-block-with-attachment\"\u003e\u003cspan\u003eRather than diving into specific software libraries, Huyen guides readers through the complex architectural trade-offs that dictate production success. She breaks down how to choose between batch prediction and low-latency \u003cb data-path-to-node=\"7\" data-index-in-node=\"223\"\u003estreaming inference\u003c\/b\u003e, how to avoid catastrophic \u003cb data-path-to-node=\"7\" data-index-in-node=\"270\"\u003edata leakage\u003c\/b\u003e during feature engineering, and how to detect the silent killer of AI applications: \u003cb data-path-to-node=\"7\" data-index-in-node=\"367\"\u003edata drift\u003c\/b\u003e and \u003cb data-path-to-node=\"7\" data-index-in-node=\"382\"\u003econcept drift\u003c\/b\u003e. From selecting training data sizes to deploying models across edge devices or multi-cloud infrastructures, the text provides structured, real-world case studies from major tech enterprises to show how resilient, self-correcting ML systems are engineered.\u003c\/span\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"7\"\u003e\u003cspan class=\"text-block-with-attachment\"\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c!----\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cdiv class=\"code-block ng-tns-c3299913081-87 ng-animate-disabled ng-trigger ng-trigger-codeBlockRevealAnimation\" data-hveid=\"0\" data-ved=\"0CAAQhtANahgKEwjvvJOByMeUAxUAAAAAHQAAAAAQoQI\"\u003e\n\u003c!----\u003e\n\u003cdiv class=\"formatted-code-block-internal-container ng-tns-c3299913081-87\"\u003e\n\u003cdiv class=\"animated-opacity ng-tns-c3299913081-87\"\u003e\n\u003c!----\u003e\n\u003cp data-path-to-node=\"30\"\u003eAs our regional tech ecosystem enters a highly sophisticated phase—with local software teams rolling out automated financial apps, real-time e-commerce recommendation engines, and digital logistics platforms—engineers are hitting a massive operational wall. While many local developers can easily train a predictive model in an isolated notebook, very few know how to scale that model to serve millions of requests without breaking corporate cloud budgets or suffering severe performance degradation.\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eLanguage: English.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eGenre: Software Engineering.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eBinding: সেলাই করা বাইন্ডিং\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eQuality: Premium Quality Books.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePrinting: High Quality Printing.\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003ePaper: Eye Friendly paper (Cream White)\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003cstrong\u003eCover: Matt cover (Paperback).\u003c\/strong\u003e\u003c\/span\u003e\u003c\/p\u003e\n\u003cp data-path-to-node=\"31\"\u003e \u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e","brand":"Royal Books BD","offers":[{"title":"Default Title","offer_id":47228302131385,"sku":null,"price":350.0,"currency_code":"BDT","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0780\/0874\/6169\/files\/Designing_Machine_Learning_Systems.jpg?v=1779276022","url":"https:\/\/royalbooksbd.com\/products\/designing-machine-learning-systems","provider":"Royal Books BD","version":"1.0","type":"link"}