Hands-On Artificial Intelligence with TensorFlow
Useful techniques in machine learning and deep learning for building intelligent applications
Published on 31. October 2018
Book
Paperback/Softback
582 pages
978-1-78899-807-9 (ISBN)
Description
Exploit TensorFlow's capabilities to build artificial intelligence applications
Key Features
Exploit TensorFlow's new features to power your artificial intelligence apps
Implement machine learning, deep learning, and reinforcement learning models with Tensorflow
Build intelligent applications for computer vision, NLP, and healthcare, among others
Book DescriptionArtificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more.
Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques. In addition to this, the book covers advanced concepts, such as reinforcement learning, generative adversarial networks (GANs), and multimodal learning.
Once you have grasped all this, you'll move on to exploring GPU computing and neuromorphic computing, along with the latest trends in quantum computing. You'll work through case studies that will help you examine AI applications in the important areas of computer vision, healthcare, and FinTech, and analyze their datasets. In the concluding chapters, you'll briefly investigate possible developments in AI that we can expect to see in the future.
By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow.
What you will learn
Explore the core concepts of AI and its different approaches
Use the TensorFlow framework for smart applications
Implement various machine and deep learning algorithms with TensorFlow
Design self-learning RL systems and implement generative models
Perform GPU computing efficiently using best practices
Build enterprise-grade apps for computer vision, NLP, and healthcare
Who this book is forHands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.
Key Features
Exploit TensorFlow's new features to power your artificial intelligence apps
Implement machine learning, deep learning, and reinforcement learning models with Tensorflow
Build intelligent applications for computer vision, NLP, and healthcare, among others
Book DescriptionArtificial Intelligence (AI) is a popular area with an emphasis on creating intelligent machines that can reason, evaluate, and understand the same way as humans. It is used extensively across many fields, such as image recognition, robotics, language processing, healthcare, finance, and more.
Hands-On Artificial Intelligence with TensorFlow gives you a rundown of essential AI concepts and their implementation with TensorFlow, also highlighting different approaches to solving AI problems using machine learning and deep learning techniques. In addition to this, the book covers advanced concepts, such as reinforcement learning, generative adversarial networks (GANs), and multimodal learning.
Once you have grasped all this, you'll move on to exploring GPU computing and neuromorphic computing, along with the latest trends in quantum computing. You'll work through case studies that will help you examine AI applications in the important areas of computer vision, healthcare, and FinTech, and analyze their datasets. In the concluding chapters, you'll briefly investigate possible developments in AI that we can expect to see in the future.
By the end of this book, you will be well-versed with the essential concepts of AI and their implementation using TensorFlow.
What you will learn
Explore the core concepts of AI and its different approaches
Use the TensorFlow framework for smart applications
Implement various machine and deep learning algorithms with TensorFlow
Design self-learning RL systems and implement generative models
Perform GPU computing efficiently using best practices
Build enterprise-grade apps for computer vision, NLP, and healthcare
Who this book is forHands-On Artificial Intelligence with TensorFlow is for you if you are a machine learning developer, data scientist, AI researcher, or anyone who wants to build artificial intelligence applications using TensorFlow. You need to have some working knowledge of machine learning to get the most out of this book.
More details
Language
English
Place of publication
Birmingham
United Kingdom
Target group
Professional and scholarly
Dimensions
Height: 92 mm
Width: 75 mm
ISBN-13
978-1-78899-807-9 (9781788998079)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Amir Ziai is a senior data scientist at Netflix, where he works on streaming security involving petabyte-scale machine learning platforms and applications. He has worked as a data scientist in AdTech, HealthTech, and FinTech companies. He holds a master's degree in data science from UC Berkeley. Ankit Dixit is a deep learning expert at AIRA Matrix in Mumbai, India and having an experience of 7 years in the field of computer vision and machine learning. He is currently working on the development of full slide medical image analysis solutions in his organization. His work involves designing and implementation of various customized deep neural networks for image segmentation as well as classification tasks. He has worked with different deep neural network architectures such as VGG, ResNet, Inception, Recurrent Neural Nets (RNN) and FRCNN. He holds a masters degree in computer vision specialization. He has also authored an AI/ML book.
Content
Table of Contents
Overview of AI
TensorFlow for Artificial Intelligence
Approaches to Solving AI
Computer Vision and Intelligence
Computational Understanding of Natural Language
Reinforcement Learning
Generative Adversarial Networks
Multimodal Learning
From GPUs to Quantum Computing - AI Hardware
TenserFlow Serving
AI Applications in Healthcare
AI Applications in Business
Overview of AI
TensorFlow for Artificial Intelligence
Approaches to Solving AI
Computer Vision and Intelligence
Computational Understanding of Natural Language
Reinforcement Learning
Generative Adversarial Networks
Multimodal Learning
From GPUs to Quantum Computing - AI Hardware
TenserFlow Serving
AI Applications in Healthcare
AI Applications in Business