DEEP LEARNING USING PYTHON

Publisher:
WILEY INDIA
| Author:
Dr. D Karthika Renuka Dr. S Lovelyn Rose, Dr. L Ashok Kumar
| Language:
English
| Format:
Paperback
Publisher:
WILEY INDIA
Author:
Dr. D Karthika Renuka Dr. S Lovelyn Rose, Dr. L Ashok Kumar
Language:
English
Format:
Paperback

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SKU 9788126579914 Category
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The book has been divided into seven chapters. chapter 1 elaborately deals with the fundamentals of deep learning, to enable any reader to understand the deep learning architectures elaborated in subsequent chapters. chapter 2 deals with convolutional neural networks (cnns), which have proven to be very effective in the area of computer vision. chapter 3 deals with recurrent neural networks (runs) and its variants. The various types of autoencoders, which are a type of artificial neural network used to learn efficient data Encoding, are presented in Chapter 4. To learn the probability distribution over the set of inputs, restricted Boltzmann machine (RBI) is discussed in Chapter 5. chapter 6 presents popular open source frameworks in Python for deep learning applications. chapter 7 describes how to utilize the knowledge that you have gained from previous chapters in real-time applications.

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Description

The book has been divided into seven chapters. chapter 1 elaborately deals with the fundamentals of deep learning, to enable any reader to understand the deep learning architectures elaborated in subsequent chapters. chapter 2 deals with convolutional neural networks (cnns), which have proven to be very effective in the area of computer vision. chapter 3 deals with recurrent neural networks (runs) and its variants. The various types of autoencoders, which are a type of artificial neural network used to learn efficient data Encoding, are presented in Chapter 4. To learn the probability distribution over the set of inputs, restricted Boltzmann machine (RBI) is discussed in Chapter 5. chapter 6 presents popular open source frameworks in Python for deep learning applications. chapter 7 describes how to utilize the knowledge that you have gained from previous chapters in real-time applications.

About Author

Dr. S. Lovelyn Rose completed her PhD with Anna University, Chennai, under the faculty of Information and Communication Engineering. Her professional career of 16 years has been with PSG College of Technology. She has authored a book Data Structures, which has been very well received. She has several publications in national and international journals and conferences. Her subject expertise and interests include data structures and algorithms, algorithm design techniques, machine learning and deep learning. She has been a keynote speaker and resource person for various national and international conferences and workshops in her area of expertise. Dr. L. Ashok Kumar is presently working as a Professor and Associate HoD in the Department of EEE, PSG College of Technology. He is a recipient of the BHAVAN fellowship from the Indo-US Science and Technology Forum and SYST Fellowship from DST, Govt. of India. He has 3 years of industrial experience and 19 years of academic and research experience. He has published 187 technical papers in international and national journals and presented 197 papers in national and international conferences. He has completed 27 Government of India-funded projects, and currently 5 projects are in progress. Dr. D. Karthika Renuka is working as Associate Professor in Department of Information Technology, PSG College of Technology. Her professional career of 15 years has been with PSG College of Technology. Her area of specialization includes Data Mining, Evolutionary Algorithms, Machine Learning and Deep Learning. She has organized an International Conference, a National Conference and several workshops. She is a reviewer for Computer and Electrical Engineering, Elsevier, Wiley book chapters, Springer Book Chapters “Knowledge Computing and its Applications”. She has published several papers in reputed national and international journals and conferences.

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