<p>This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture wi
Machine Learning and Deep Learning in Real-Time Applications
β Scribed by Paawan Sharma, Kamal Kant Hiran, Gaurav Meena, Mehul Mahrishi
- Year
- 2020
- Tongue
- English
- Leaves
- 364
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Table of Contents
Title Page
Copyright Page
Book Series
Editorial Advisory Board
Table of Contents
Detailed Table of Contents
Foreword
Preface
Acknowledgment
Chapter 1: Obtaining Deep Learning Models for Automatic Classification of Leukocytes
Chapter 2: Deep Leaning Using Keras
Chapter 3: Deep Learning With PyTorch
Chapter 4: Deep Learning With TensorFlow
Chapter 5: Employee's Attrition Prediction Using Machine Learning Approaches
Chapter 6: A Novel Deep Learning Method for Identification of Cancer Genes From Gene Expression Dataset
Chapter 7: Machine Learning in Authentication of Digital Audio Recordings
Chapter 8: Deep Convolutional Neural Network-Based Analysis for Breast Cancer Histology Images
Chapter 9: Deep Learning in Engineering Education
Chapter 10: Malaria Detection System Using Convolutional Neural Network Algorithm
Chapter 11: An Introduction to Deep Convolutional Neural Networks With Keras
Chapter 12: Emotion Recognition With Facial Expression Using Machine Learning for Social Network and Healthcare
Chapter 13: Text Separation From Document Images
Compilation of References
About the Contributors
Index
π SIMILAR VOLUMES
<p>This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture wi
With the emergence of revolutionary technological standards such as 5G and Industry 4.0, real time applications which require both cloud computing and machine learning are becoming increasingly common. Examples of such applications include real-time scheduling and resource allocation in cloud radio
<span><p>This book introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary ML/DL research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for healthcare sector, it depth, brea
<p><span>This book is very beneficial for early researchers/faculty who want to work in deep learning and machine learning for the classification domain. It helps them study, formulate, and design their research goal by aligning the latest technologies studiesβ image and data classifications. The ea