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Description：
Most data scientists and engineers today rely on quality labeled data to train their machine learning models. But building training sets manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There’s a more practical approach. In this book, Amit Bahree, Senja Filipi, and Wee Hyong Tok from Microsoft show you how to create products using weakly supervised learning models.
You’ll learn how to build natural language p...
Description：
Transfer Learning for Natural Language Processing gets you up to speed with the relevant ML concepts before diving into the cutting-edge advances that are defining the future of NLP.
Building and training deep learning models from scratch is costly, time-consuming, and requires massive amounts of data. To address this concern, cutting-edge transfer learning techniques enable you to start with pretrained models you can tweak to meet your exact needs. In ...
Description：
In Machine Learning Bookcamp you’ll learn the essentials of machine learning by completing a carefully designed set of real-world projects.
The only way to learn is to practice! In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects.
In Machine Learning Bookcamp you’ll learn the essentials of machine learning by completing a carefully designed set of real-world pr...
Description：
Develop neural network applications using the Java environment. After learning the rules involved in neural network processing, this second edition shows you how to manually process your first neural network example. The book covers the internals of front and back propagation and helps you understand the main principles of neural network processing. You also will learn how to prepare the data to be used in neural network development and you will be able t...
Description:
By using machine learning models to extract information from images, organizations today are making breakthroughs in healthcare, manufacturing, retail, and other industries. This practical book shows ML engineers and data scientists how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques.
Google engineers Valliappa Lakshmanan, Martin Garner, ...
Description：
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.
Current and aspiring machine learning engineers–or anyone familiar with data science and ...
Description:
Machine Learning: A Bayesian and Optimization Perspective, 2nd edition, gives a unified perspective on machine learning by covering both pillars of supervised learning, namely regression and classification. The book starts with the basics, including mean square, least squares and maximum likelihood methods, ridge regression, Bayesian decision theory classification, logistic regression, and decision trees. It then progresses to more recent techniques, coveri...
内容简介：
AlphaGo战胜了世界围棋冠军，但无论是聂卫平还是设计AlphaGo的谷歌工程师都无法理解AlphaGo为什么这样走棋，这就是人工智能中令人困惑的“不可解释性”问题。作者从这个问题出发，发现了一类全新的知识——“暗知识”。
一直以来人类的知识可以分为两类：“明知识”和“默知识”。明知识就是那些可以用语言、文字或公式清晰表达和描述的知识；默知识则是个人在感觉上能把握但无法清晰描述的知识，也即我们常说的“只可意会，不可言传”的那类知识。今天，人工智能突然发掘出了人类既无法感受又无法表达...
Description:
Some people believe that artificial intelligence (AI) will revolutionize modern life in ways that improve human existence. Others say that the promise of AI is overblown. Still others contend that AI applications could pose a grave threat to the economic security of millions of people by taking their jobs and otherwise rendering them “obsolete”–or, even worse, that AI could actually spell the end of the human race.
This volume will help users understan...
Description：
Deploying a machine learning model into a fully realized production system usually requires painstaking work by an operations team creating and managing custom servers. Cloud Native Machine Learning helps you bridge that gap by using the pre-built services provided by cloud platforms like Azure and AWS to assemble your ML system’s infrastructure.
Deploying a machine learning model into a fully realized production system usually requires painstaking wo...
Description：
Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development avoids constraints found in traditional machine learning (ML) algorithms. This practical book shows data science and AI professionals how to learn by reinforcement and enable a machine to learn by itself.
Author Phil Winder of Winder Research cove...
