Machine Learning, Data Science, and AI Engineering with Python: Build real world ML pipelines, deploy LLM in production, and scale AI applications with Python

by Frank Kane, Gabriel Preda

Build complete machine learning and AI solutions with Python, from modeling and LLMs to deployment and MLOps.



Free with your PDF Copy, AI Assistant, and Next-Gen Reader

Key FeaturesBuild AI systems from data prep to LLM deploymentLearn RAG pipelines, Context engineering, Agentic AI, and real MLOps toolsApply each concept using practical Python projectsBook DescriptionMachine Learning, Data Science, and AI Engineering with Python teaches you how to build and ship production-ready AI systems. Starting from core concepts in machine learning, data science, and Python tooling, you’ll move through deep learning, Transformers, and large language models to master advanced tools like retrieval-augmented generation (RAG), LLM agents, and responsible AI workflows.

With each chapter building toward a complete machine learning pipeline, you’ll gain hands-on experience with tools like PyTorch, MLflow, DVC, and FastAPI. You'll also explore key production skills such as model versioning, A/B testing, and containerized deployment.

By the end of this book, you’ll know how to take a raw dataset and develop, evaluate, and deploy real time AI systems that are robust, scalable, and explainable.

What you will learnTrain ML models using scikit-learn and PyTorchBuild deep learning systems for vision and NLP tasksIntegrate and fine-tune Transformer-based LLMsConstruct RAG pipelines using vector databasesDevelop and deploy APIs with FastAPI and DockerManage models and experiments with MLflow and DVCBuild LLM agents using OpenAI, Gemini, LangGraph and ADKApply fairness and interpretability to ML pipelinesWho this book is forThis book is for aspiring machine learning engineers, data scientists, and developers looking to gain real-world AI skills. Readers will go from Python basics to full-stack AI development, including model deployment, MLOps, and cutting-edge LLM integrations.

Table of ContentsIntroduction to Data Science and the Python EcosystemStatistics, Probability, and Linear ModelsCore Machine Learning AlgorithmsFeature Engineering and Data PreprocessingIntroduction to Neural NetworksBuilding and Training Deep NetworksComputer Vision with Convolutional NetworksTransformers and Modern NLPRecommender SystemsEvaluating and Interpreting ModelsOptimization and Experiment TrackingDeploying Models into ProductionScaling, Automation, and MLOps PipelinesGenerative Models and AutoencodersLarge Language Models and RAG SystemsBuilding LLM Agents and Multi-Agent SystemsEthics, Fairness, and Responsible AI

Kindle Edition

Expected publication October 9, 2026

About the author

Frank Kane, Brooklyn-born and a lifetime New Yorker, worked for many years in journalism and corporate public relations before shifting to fiction writing. At the time he was selling crime stories to the pulps he was also sustaining a career writing scripts for such radio shows as Gangbusters and The Shadow.

In addition to the Johnny Liddells, Kane wrote several suspense novels, some softcore erotica, and (under the pen name of Frank Boyd) "Johnny Staccato", a Gold Medal original paperback based on the short-lived noir television series, starring John Cassavetes, about a Greenwich Village bebop pianist turned private detective.