Deep Learning with Azure: Building and Deploying Artificial Intelligence Solutions on the Microsoft AI Platform

Description

Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll LearnBecome familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful. Front Matter ....Pages i-xxvii Front Matter ....Pages 1-1 Introduction to Artificial Intelligence (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 3-26 Overview of Deep Learning (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 27-51 Trends in Deep Learning (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 53-75 Front Matter ....Pages 77-77 Microsoft AI Platform (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 79-98 Cognitive Services and Custom Vision (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 99-128 Front Matter ....Pages 129-129 Convolutional Neural Networks (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 131-160 Recurrent Neural Networks (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 161-186 Generative Adversarial Networks (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 187-208 Front Matter ....Pages 209-209 Training AI Models (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 211-241 Operationalizing AI Models (Mathew Salvaris, Danielle Dean, Wee Hyong Tok)....Pages 243-259 Back Matter ....Pages 261-284