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Machine Learning Engineering

By Henry Codwell

Machine Learning Engineering

By Henry Codwell

0 - Default Title
Description
Turn your machine learning knowledge into real-world solutions with this comprehensive, project-based guide designed for data scientists, software engineers, and AI practitioners looking to transition from experimentation to production.This hands-on guide walks you through the development of 50 fully functional machine learning models, covering a wide range of industries and applications-including finance, healthcare, e-commerce, NLP, computer vision, recommendation systems, and time-series forecasting. Each project is engineered to mirror real-world workflows, with an emphasis on scalability, performance, and deployment.You'll learn to integrate cutting-edge tools such as TensorFlow, Scikit-learn, FastAPI, Docker, Kubernetes, and MLflow into your pipelines, while mastering MLOps practices that ensure reliability, reproducibility, and maintainability of models in production environments.Key features include:End-to-end development of 50 machine learning projectsGuidance on production-ready model design, training, testing, and deploymentStep-by-step implementation using Python, with clean, reusable codeReal-world datasets and scalable architecturesCoverage of key MLOps tools and CI/CD automation strategies
Whether you're aiming to build your portfolio, advance your career, or deploy robust machine learning systems, this book gives you the practical skills and tools to succeed.
Product details
Binding:
Paperback
Number of Pages:
318
Release Date:
2025-07-21
Publication Date:
2025-07-21
Publisher:
MARTIN CHAVEZ
Languages:
Original: English
ISBN13:
9798231388882
Weight:
402 g
Height:
140 cm
Width:
216 cm
Thickness:
17 cm
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