Catalog Search Results
Author
Pub. Date
2022.
Language
English
Description
Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization. By applying...
Author
Pub. Date
2022.
Language
English
Description
Explore supercharged machine learning techniques to take care of your data laundry loads Key Features Learn how to prepare data for machine learning processes Understand which algorithms are based on prediction objectives and the properties of the data Explore how to interpret and evaluate the results from machine learning Book Description Many individuals who know how to run machine learning algorithms do not have a good sense of the statistical...
104) Kikai gakushū dezain patān: dēta junbi, moderu kōchiku, MLOps no jissenjō no mondai to kaiketsu
Author
Pub. Date
2021.
Language
日本語
Author
Pub. Date
2022.
Language
Deutsch
Description
Dieses Buch ist ein umfassender Leitfaden für das Verständnis von Datenanalyse am Arbeitsplatz. Alex Gutman und Jordan Goldmeier lüften den Vorhang der Data Science und geben Ihnen die Sprache und die Werkzeuge an die Hand, die Sie benötigen, um informiert mitreden zu können, kritisch über die Auswertung von Daten zu sprechen und die richtigen Fragen zu stellen. Dank dieses Buchs kann jede:r ein Data Head werden und aktiv an Data Science,...
Author
Pub. Date
2021.
Language
English
Description
Until recently, an organization would have had to collect and store data in a central location to train a model with machine learning. Now, federated learning offers an alternative. With this report, you'll learn how to train ML models without sharing sensitive data in the process. Google software engineers Emily Glanz and Nova Fallen introduce the motivation and technologies behind federated learning, providing the context you need to integrate it...
Author
Pub. Date
2020.
Language
English
Description
Machine learning is the key to digital transformation for many businesses today. This process accelerates your company's ability to engage customers, optimize operations, empower employees, and fundamentally change and transform products. One of the best ways to get started is with Automated Machine Learning, a quick and efficient method to jumpstart your organization's use of machine learning. In this report, AI leader Wee Hyong Tok explains how...
108) Not with a bug, but with a sticker: attacks on machine learning systems and what to do about them
Author
Pub. Date
2023.
Language
English
Description
A robust and engaging account of the single greatest threat faced by AI and ML systems In Not With A Bug, But With A Sticker: Attacks on Machine Learning Systems and What To Do About Them, a team of distinguished adversarial machine learning researchers deliver a riveting account of the most significant risk to currently deployed artificial intelligence systems: cybersecurity threats. The authors take you on a sweeping tour - from inside secretive...
Pub. Date
2023.
Language
English
Description
AUTONOMOUS VEHICLES Addressing the current challenges, approaches and applications relating to autonomous vehicles, this groundbreaking new volume presents the research and techniques in this growing area, using Internet of Things (IoT), Machine Learning (ML), Deep Learning, and Artificial Intelligence (AI). This book provides and addresses the current challenges, approaches, and applications relating to autonomous vehicles, using Internet of Things...
Author
Pub. Date
2019.
Language
English
Description
With Early Release ebooks, you get books in their earliest form-the author's raw and unedited content as he or she writes-so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. With detailed notes, tables, and examples, this handy reference will help you navigate the basics of...
Author
Pub. Date
[2020]
Language
English
Description
Understand the industrialization of machine learning (ML) and take the first steps toward identifying and generating the transformational disruptors of artificial intelligence (AI). You will learn to apply ML to data lakes in various industries, supplying data professionals with the advanced skills required to handle the future of data engineering and data science. Data lakes currently generated by worldwide industrialized business activities are...
Author
Pub. Date
2021
Language
English
Description
Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices. Machine learning (ML) can be an intimidating subject until you know the essentials and for what applications it works. This book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language such as JavaScript to work with more approachable, fundamental coding ideas. Using JavaScript programming...
Author
Pub. Date
2022.
Language
English
Description
Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using...
Author
Pub. Date
©2020
Language
English
Description
Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented...
Author
Series
Language
English
Description
This book provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. It contains a breakdown of each ML variant, explaining how it works and how it is used within certain industries, allowing readers to incorporate the presented techniques into their own work as they follow along. It is an accessible, comprehensive guide for the non-mathematician, providing...
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