Applied Deep Leaing: Design and implement your own Neural Networks to solve real-world problems (English Edition)

by: Dr. Rajkumar Tekchandani (Author),Dr. Neeraj Kumar(Author)

Publication Date: 2023/4/29

Language: English

Print Length: 624 pages

ISBN-10: 9355513720

ISBN-13: 9789355513724

Book Description

A comprehensive guide to Deep Leaing for BeginnersKey Features● Lea how to design your own neural network efficiently.● Lea how to build and train Recurrent Neural Networks (RNNs).● Understand how encoding and decoding work in Deep Neural Networks.DescriptionDeep Leaing has become increasingly important due to the growing need to process and make sense of vast amounts of data in various fields. If you want to gain a deeper understanding of the techniques and implementations of deep leaing, then this book is for you.The book presents you with a thorough introduction to AI and Machine leaing, starting from the basics and progressing to a comprehensive coverage of Deep Leaing with Python. You will be introduced to the intuition of Neural Networks and how to design and train them effectively. Moving on, you will lea how to use Convolutional Neural Networks for image recognition and other visual tasks. The book then focuses on localization and object detection, which are crucial tasks in many applications, including self-driving cars and robotics. You will also lea how to use Deep Leaing algorithms to identify and locate objects in images and videos. In addition, you will gain knowledge on how to create and train Recurrent Neural Networks (RNNs), as well as explore more advanced variations of RNNs. Lastly, you will lea about Generative Adversarial Networks (GAN), which are used for tasks like image generation and style transfer.What you will lea● Lea how to work efficiently with various Convolutional models.● Lea how to utilize the You Only Look Once (YOLO) framework for object detection and localization.● Understand how to use Recurrent Neural Networks for Sequence Leaing.● Lea how to solve the vanishing gradient problem with LSTM.● Distinguish between fake and real images using various Generative Adversarial Networks.Who this book is forThis book is intended for both current and aspiring Data Science and AI professionals, as well as students of engineering, computer applications, and masters programs interested in Deep leaing.Table of Contents1. Basics of Artificial Intelligence and Machine Leaing2. Introduction to Deep Leaing with Python3. Intuition of Neural Networks4. Convolutional Neural Networks5. Localization and Object Detection6. Sequence Modeling in Neural Networks and Recurrent Neural Networks (RNN)7. Gated Recurrent Unit, Long Short-Term Memory, and Siamese Networks8. Generative Adversarial Networks

About the Author

A comprehensive guide to Deep Leaing for BeginnersKey Features● Lea how to design your own neural network efficiently.● Lea how to build and train Recurrent Neural Networks (RNNs).● Understand how encoding and decoding work in Deep Neural Networks.DescriptionDeep Leaing has become increasingly important due to the growing need to process and make sense of vast amounts of data in various fields. If you want to gain a deeper understanding of the techniques and implementations of deep leaing, then this book is for you.The book presents you with a thorough introduction to AI and Machine leaing, starting from the basics and progressing to a comprehensive coverage of Deep Leaing with Python. You will be introduced to the intuition of Neural Networks and how to design and train them effectively. Moving on, you will lea how to use Convolutional Neural Networks for image recognition and other visual tasks. The book then focuses on localization and object detection, which are crucial tasks in many applications, including self-driving cars and robotics. You will also lea how to use Deep Leaing algorithms to identify and locate objects in images and videos. In addition, you will gain knowledge on how to create and train Recurrent Neural Networks (RNNs), as well as explore more advanced variations of RNNs. Lastly, you will lea about Generative Adversarial Networks (GAN), which are used for tasks like image generation and style transfer.What you will lea● Lea how to work efficiently with various Convolutional models.● Lea how to utilize the You Only Look Once (YOLO) framework for object detection and localization.● Understand how to use Recurrent Neural Networks for Sequence Leaing.● Lea how to solve the vanishing gradient problem with LSTM.● Distinguish between fake and real images using various Generative Adversarial Networks.Who this book is forThis book is intended for both current and aspiring Data Science and AI professionals, as well as students of engineering, computer applications, and masters programs interested in Deep leaing.Table of Contents1. Basics of Artificial Intelligence and Machine Leaing2. Introduction to Deep Leaing with Python3. Intuition of Neural Networks4. Convolutional Neural Networks5. Localization and Object Detection6. Sequence Modeling in Neural Networks and Recurrent Neural Networks (RNN)7. Gated Recurrent Unit, Long Short-Term Memory, and Siamese Networks8. Generative Adversarial Networks