{"product_id":"machine-learning-engineering-with-python-manage-the-production-life-cycle-of-machine-learning-models-using-mlops-with-practical-examples-paperback","title":"Machine Learning Engineering with Python: Manage the production life cycle of machine learning models using MLOps with practical examples - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAndrew P. McMahon\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eSupercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eExplore hyperparameter optimization and model management tools\u003c\/li\u003e\n\u003cli\u003eLearn object-oriented programming and functional programming in Python to build your own ML libraries and packages\u003c\/li\u003e\n\u003cli\u003eExplore key ML engineering patterns like microservices and the Extract Transform Machine Learn (ETML) pattern with use cases\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBook Description: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eMachine learning engineering is a thriving discipline at the interface of software development and machine learning. This book will help developers working with machine learning and Python to put their knowledge to work and create high-quality machine learning products and services.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eMachine Learning Engineering with Python takes a hands-on approach to help you get to grips with essential technical concepts, implementation patterns, and development methodologies to have you up and running in no time. You'll begin by understanding key steps of the machine learning development life cycle before moving on to practical illustrations and getting to grips with building and deploying robust machine learning solutions. As you advance, you'll explore how to create your own toolsets for training and deployment across all your projects in a consistent way. The book will also help you get hands-on with deployment architectures and discover methods for scaling up your solutions while building a solid understanding of how to use cloud-based tools effectively. Finally, you'll work through examples to help you solve typical business problems.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eBy the end of this book, you'll be able to build end-to-end machine learning services using a variety of techniques and design your own processes for consistently performant machine learning engineering.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat You Will Learn: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eFind out what an effective ML engineering process looks like\u003c\/li\u003e\n\u003cli\u003eUncover options for automating training and deployment and learn how to use them\u003c\/li\u003e\n\u003cli\u003eDiscover how to build your own wrapper libraries for encapsulating your data science and machine learning logic and solutions\u003c\/li\u003e\n\u003cli\u003eUnderstand what aspects of software engineering you can bring to machine learning\u003c\/li\u003e\n\u003cli\u003eGain insights into adapting software engineering for machine learning using appropriate cloud technologies\u003c\/li\u003e\n\u003cli\u003ePerform hyperparameter tuning in a relatively automated way\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eThis book is for machine learning engineers, data scientists, and software developers who want to build robust software solutions with machine learning components. If you're someone who manages or wants to understand the production life cycle of these systems, you'll find this book useful. Intermediate-level knowledge of Python is necessary.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 276\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.58 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e November 05, 2021\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47213196181753,"sku":"9781801079259","price":83.5,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0789\/2782\/3097\/files\/RmVCLzhSQkJWeWdoVlNGcUpMNzFOQT09.webp?v=1768104285","url":"https:\/\/bookscloud.io\/products\/machine-learning-engineering-with-python-manage-the-production-life-cycle-of-machine-learning-models-using-mlops-with-practical-examples-paperback","provider":"BooksCloud Book Dropshipping","version":"1.0","type":"link"}