Hands-On Artificial Intelligence with TensorFlow (eBook, ePUB)
Useful techniques in machine learning and deep learning for building intelligent applications
PAYBACK Punkte
0 °P sammeln!
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, ...
Exploit TensorFlow's capabilities to build artificial intelligence applications
Artificial 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.
Hands-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.
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.
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 Description
Artificial 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 for
Hands-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.
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.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Andere Kunden interessierten sich für
