{"product_id":"ml-optimization-techniques-boosting-model-performance-fine-tune-ml-models-for-accuracy-and-computational-efficiency-9798265144638","title":"ML Optimization Techniques Boosting Model Performance: Fine-tune ML models for accuracy and computational efficiency","description":"\u003cp\u003e • Author(s): Isandro Myles\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Software Development \u0026amp; Engineering - General\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eSpeed and accuracy aren't enemies-they're a design choice. \u003cb\u003eML Optimization Techniques: Boosting Model Performance\u003c\/b\u003e is your practical playbook for squeezing more signal from the same data, cutting training time, and shipping models that perform where it counts: in production.\u003c\/p\u003e\u003cp\u003eInside, you'll move beyond \"try a bigger model\" to a systematic approach that stacks small, compounding wins-better data splits, smarter tuning, tighter regularization, faster math, and leaner deployments. You'll learn what to measure, which knobs matter most, and how to make trade-offs you can defend to stakeholders.\u003c\/p\u003e\u003cp\u003eWhat you'll be able to do: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eChoose and tune optimizers (SGD, AdamW, LBFGS) with schedules that actually converge\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eRun \u003cb\u003eBayesian\u003c\/b\u003e, random, and evolutionary searches that beat grid search with fewer trials\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eAvoid leakage with robust CV schemes and fail-fast early stopping\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eBoost generalization with regularization, augmentation, and calibrated probability outputs\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eFix class imbalance (weights, focal loss, stratified sampling) without skewing metrics\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eStack and blend models the right way (OOF folds, diversity, calibration)\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eCompress models (pruning, quantization, distillation) for edge and low-latency serving\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eAccelerate training with mixed precision, vectorization, caching, and efficient data loaders\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eProfile bottlenecks (CPU\/GPU, I\/O) and pick wins that matter for wall-clock time\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eOperate with MLOps discipline: champion\/challenger, drift monitoring, rollback plans\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eWritten for data scientists, ML engineers, and practitioners who care about results, this book favors clarity over hype and repeatable techniques over lucky runs.\u003c\/p\u003e","brand":"Atlantic Books","offers":[{"title":"Paperback","offer_id":46332691447959,"sku":"9798265144638","price":1654.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798265144638.webp?v=1767715503","url":"https:\/\/atlanticbooks.com\/products\/ml-optimization-techniques-boosting-model-performance-fine-tune-ml-models-for-accuracy-and-computational-efficiency-9798265144638","provider":"Atlantic Books","version":"1.0","type":"link"}