Deep Learning and its Applications using Python - Tapa dura

Acerca del autor

Niha Kamal Basha is an assistant professor in the Department of Information Security, School of Computer Science and Engineering, Vellore Institute of Science and Technology, India. She has received a number of awards and published numerous research articles in peer-reviewed journals.

Surbhi Bhatia, PhD, is an assistant professor in the Department of Information Systems, College of Computer Sciences and Information Technology, King Faisal University, Saudi Arabia. She has more than 10 years of teaching experience in different universities in India and Saudi Arabia. She has published many articles in peer-reviewed journals, authored or edited 9 books, and has been granted 8 national and international patents.

Abhishek Kumar gained his PhD in computer science from the University of Madras, India in 2019. He is assistant director/associate professor in the Computer Science & Engineering Department, Chandigarh University, Punjab, India. He has more than 100 publications in peer-reviewed international and national journals, books & conferences. His research interests include artificial intelligence, image processing, computer vision, data mining, and machine learning.

Arwa Mashat, gained her PhD in Instructional Design and Technology from Old Dominion University, Virginia, USA in 2017. She has a rich 14 years of teaching and academic experience. She is currently an assistant professor at the College of Computing and Information Technology, King Abdulaziz University, Saudi Arabia. She is currently the Vice Dean for two colleges; the College of Computing and Information Technology and the Applied College at King Abdulaziz University. She has published many research papers in reputed journals.

De la contraportada

This practical book gives a detailed description of deep learning models and their implementation using Python programming relating to computer vision, natural language processing, and other applications.

This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing deep learning application models. It also identifies future research directions for deep learning. Readers/users will discover

• A precise description of deep learning history, fundamental concepts, and background information relating to deep learning;
• A detailed introduction to several concepts including tensorflow and keras, starting from the fundamentals to the application-based concept implementation using Python;
• Explanations of multilayer perceptron, convolutional neural network, recurrent neural network, and long short-term memory in terms of applications like chatbot, face detection and recognition;
• Advanced deep learning concepts along with their future research advancements;
• Assist in building the reader's understanding through intuitive explanations and practical examples by exploring challenging concepts in the related applications of computer vision, natural language processing, and other models.

Audience

The book is ideal for computer science researchers, industry professionals, as well as postgraduate and undergraduate students who want to learn how to program deep learning models using Python.