{"product_id":"from-models-to-mastery-building-classical-deep-learning-systems-with-pytorch-scikit-learn-and-python-9798292377696","title":"From Models to Mastery: Building Classical \u0026 Deep Learning Systems with PyTorch, Scikit-Learn, and Python","description":"\u003cp\u003e • Author(s): Alira Vexel\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Languages - Python\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003cb\u003eFrom Models to Mastery: Building Classical \u0026amp; Deep Learning Systems with PyTorch, Scikit-Learn, and Python\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eUnlock the Full Power of Machine Learning - From Foundational Algorithms to Modern LLMs, Vision Transformers, and Production-Ready MLOps\u003c\/b\u003e\u003cbr\u003eAre you ready to elevate your machine learning expertise and master modern AI development with the most trusted Python tools in the industry?\u003cbr\u003e\u003cb\u003eFrom Models to Mastery\u003c\/b\u003e is your \u003cb\u003ecomprehensive guide\u003c\/b\u003e to designing, building, and deploying powerful machine learning and deep learning systems using \u003cb\u003ePyTorch 2.x\u003c\/b\u003e, \u003cb\u003eScikit-Learn 1.7+\u003c\/b\u003e, and the latest open-source tools shaping the ML landscape in 2025 and beyond.\u003cbr\u003eWhether you're a data scientist, ML engineer, AI researcher, or software developer transitioning into ML, this book empowers you with a \u003cb\u003ecomplete, end-to-end roadmap\u003c\/b\u003e - from reproducible classical models to cutting-edge LLM fine-tuning, graph learning, vision systems, and scalable MLOps workflows.\u003cbr\u003e\u003cb\u003eWhat You'll Learn\u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eSet up a modern ML environment using \u003cb\u003ePoetry\u003c\/b\u003e, \u003cb\u003eConda\u003c\/b\u003e, \u003cb\u003eCUDA\u003c\/b\u003e, and GPU accelerators\u003c\/li\u003e\n\u003cli\u003ePerform clean, ethical data wrangling using \u003cb\u003ePandas\u003c\/b\u003e, \u003cb\u003ePolars\u003c\/b\u003e, \u003cb\u003eGreat Expectations\u003c\/b\u003e, and \u003cb\u003eDVC\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eMaster feature engineering with \u003cb\u003eFeaturetools\u003c\/b\u003e, \u003cb\u003eFeast\u003c\/b\u003e, \u003cb\u003eAutoencoders\u003c\/b\u003e, and \u003cb\u003eDimensionality Reduction\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eBuild robust models using \u003cb\u003eLogistic Regression\u003c\/b\u003e, \u003cb\u003eSVMs\u003c\/b\u003e, \u003cb\u003eXGBoost\u003c\/b\u003e, \u003cb\u003ek-NN\u003c\/b\u003e, and \u003cb\u003eNa�ve Bayes\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eDive deep into PyTorch with \u003cb\u003etensor operations\u003c\/b\u003e, \u003cb\u003etorch.compile\u003c\/b\u003e, and \u003cb\u003ePyTorch Lightning\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eCreate and evaluate \u003cb\u003eCNNs\u003c\/b\u003e, \u003cb\u003eTransformers\u003c\/b\u003e, \u003cb\u003eGANs\u003c\/b\u003e, \u003cb\u003eDiffusion Models\u003c\/b\u003e, and \u003cb\u003eGraph Neural Networks\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eFine-tune LLMs using \u003cb\u003eLoRA\u003c\/b\u003e, \u003cb\u003eQLoRA\u003c\/b\u003e, \u003cb\u003ePEFT\u003c\/b\u003e, and deploy RAG pipelines with Hugging Face Transformers\u003c\/li\u003e\n\u003cli\u003eOptimize and track models using \u003cb\u003eOptuna\u003c\/b\u003e, \u003cb\u003eMLflow\u003c\/b\u003e, and \u003cb\u003eRay Tune\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eServe models via \u003cb\u003eFastAPI\u003c\/b\u003e, \u003cb\u003eBentoML\u003c\/b\u003e, \u003cb\u003eTriton\u003c\/b\u003e, and deploy to edge with \u003cb\u003eTensorRT\u003c\/b\u003e, \u003cb\u003eONNX\u003c\/b\u003e, and \u003cb\u003eTinyML\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003eImplement real-world monitoring with \u003cb\u003eEvidently AI\u003c\/b\u003e, \u003cb\u003ePrometheus\u003c\/b\u003e, \u003cb\u003eModel Cards\u003c\/b\u003e, and \u003cb\u003eISO\/EU compliance\u003c\/b\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eBuilt for the 2025 AI Stack\u003c\/b\u003e\u003cbr\u003eThis book is \u003cb\u003ecompletely modernized\u003c\/b\u003e with: \u003cul\u003e\n\u003cli\u003e\u003cb\u003ePyTorch 2.x + torch.compile\u003c\/b\u003e\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eScikit-Learn 1.7+\u003c\/b\u003e, \u003cb\u003ePolars\u003c\/b\u003e, \u003cb\u003ePEFT\u003c\/b\u003e, \u003cb\u003eFlash Attention 3\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eGraph Transformers\u003c\/b\u003e, \u003cb\u003eControlNet\u003c\/b\u003e, \u003cb\u003eRLHF\/DPO\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eFeast\u003c\/b\u003e, \u003cb\u003eKubeflow\u003c\/b\u003e, \u003cb\u003eRay\u003c\/b\u003e, \u003cb\u003eArgo\u003c\/b\u003e, \u003cb\u003eGitHub Actions\u003c\/b\u003e, and more\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eWho This Book Is For\u003c\/b\u003e\u003cul\u003e\n\u003cli\u003e\n\u003cb\u003eAspiring ML practitioners\u003c\/b\u003e seeking a rigorous, modern foundation\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eSoftware engineers\u003c\/b\u003e transitioning into AI roles\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eData scientists and AI engineers\u003c\/b\u003e looking to scale their skillset with \u003cb\u003eLLMs, MLOps, and production workflows\u003c\/b\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cb\u003eEducators and researchers\u003c\/b\u003e in need of a single, trusted reference across classical and deep learning\u003c\/li\u003e\n\u003c\/ul\u003e\u003cb\u003eTake Your ML Journey From Idea to Inference\u003c\/b\u003e\u003cbr\u003eWhether you're solving tabular classification problems, fine-tuning transformers for NLP, building vision systems, or deploying fast inference pipelines to the cloud and edge-\u003cb\u003ethis book will 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