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All Indian Reprints of O'Reilly are printed in Grayscale Machine learning is no longer just a tool for data scientists. By taking advantage of recent advances in this technology, UI and UX designers can find ways to better engage with and understand their users. This O'Reilly report not only introduces you to contemporary machine learning systems, but also provides a conceptual framework to help you integrate machine-learning capabilities into your user-facing designs.
AuthorPatrick Hebron BindingPaperback
This product will be shipped on 25-11-2022
Reserve your copy without making any payment by selecting "Other Payment" option at checkout. Full Colour Edition Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this...
AuthorAurelien Geron BindingPAperback
Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.
AuthorLewis Tunstall BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case to the next. In this book, you'll learn a holistic approach to designing ML systems that are reliable, scalable, maintainable, and adaptive to changing environments and business requirements.
AuthorChip Huyen BindingPaperback
About The Authors Prof. (Dr.) Atanu Das is the HOD, Dept. of MCA, Netaji Subhash Engineering College under MAKAUT, West Bengal, India. Formerly, he was HOD, Dept. of CSE, In-Charge, Dept. of IT and Coordinator-MTech (CSE). He received his M.Sc. (Gold Medal) from The University of...
Author 1Prof. (Dr.) Atanu Das Author 2Prof. Rajkumar Patra
About The Authors Prof. (Dr.) Atanu Das is the HOD, Dept. of MCA, Netaji Subhash Engineering College under MAKAUT, West Bengal, India. Formerly, he was HOD, Dept. of CSE, In-Charge, Dept. of IT and Coordinator-MTech (CSE). He received his M.Sc. (Gold Medal) from The University of...
Author 1Prof. (Dr.) Atanu Das Author 2Prof. Rajkumar Patra
Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.
AuthorCarl Allchin BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library.
Author 1Lewis Tunstall Author 2Leandro von Werra
All Indian Reprints of O'Reilly are printed in Grayscale Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application...
Author 1Gwen Shapira Author 2Todd Palino
All Indian Reprints of O'Reilly are printed in Grayscale Getting your models into production is the fundamental challenge of machine learning. MLOps offers a set of proven principles aimed at solving this problem in a reliable and automated way. This insightful guide takes you through what MLOps is (and how it differs from DevOps) and shows you how to put it into practice to operationalize your machine learning models.
Author 1Noah Gift Author 2Alfredo Deza
All Indian Reprints of O'Reilly are printed in Grayscale   What's so special about this book? If you've read a Head First book, you know what to expect: a visually rich format designed for the way your brain works. With Head First Design Patterns, 2E you'll learn design principles and patterns in a way that won't put you to sleep, so you can get out there to solve software design problems and speak the language of patterns with others on your team.
Author 1Eric Freeman Author 2Elisabeth Robson
All Indian Reprints of O'Reilly are printed in Grayscale Site reliability engineering (SRE) is more relevant than ever. Knowing how to keepsystems reliable has become a critical skill. With this practical book, newcomers and old hatsalike will explore a broad range of conversations happening in SRE. You'll get actionable adviceon several topics, including how to adopt SRE, why SLOs matter, when you need to upgradeyour incident response, and how monitoring and observability differ.
AuthorEmil Stolarsky Author 2Jaime Woo
All Indian Reprints of O'Reilly are printed in Grayscale Algorithmic trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading.
AuthorYves Hilpisch BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides a collection of cloud native tools for different stages of a model's lifecycle, from data exploration, feature preparation, and model training to model serving. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable.  Using examples throughout the book, authors Holden Karau, Trevor Grant, Ilan Filonenko, Richard Liu, and Boris Lublinsky explain how to use Kubeflow to train and serve your machine learning models on top of Kubernetes in the cloud or in a development environment on-premises. 
AuthorTrevor Grant Author 1Holden Karau
All Indian Reprints of O'Reilly are printed in Grayscale Working with AI is complicated and expensive for many developers. That's why cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. With this book, you'll learn how to use Google's AI-powered cloud services to do everything from creating a chatbot to analyzing text, images, and video. 
Author 1Micheal Lanham BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.  You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code.   
AuthorLaurence Moroney BindingPaperback
All Indian Reprints of O'Reilly are printed in Grayscale Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You’ll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).  
AuthorHariom Tatsat Author 1Brad Lookabaugh
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. 
AuthorJeremy Howard Author 1Sylvain Gugger
All Indian Reprints of O'Reilly are printed in Grayscale The design patterns in this book capture best practices and solutions to recurring problems in machine learning. Authors Valliappa Lakshmanan, Sara Robinson, and Michael Munn catalog the first tried-and-proven methods to help engineers tackle problems that frequently crop up during the ML process. These design patterns codify the experience of hundreds of experts into advice you can easily follow. 
AuthorValliappa Lakshmanan Author 1Michael Munn
All Indian Reprints of O'Reilly are printed in Grayscale Companies are spending billions on machine learning projects, but it's money wasted if the models can't be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You'll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems.  
AuthorHannes Hapke Author 1Catherine Nelson
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