Prakash K.B., Kannan R., Alexander S.A., Kanagachidambaresan G.R. Advanced Deep Learning for Engineers and Scientists: A Practical Approach

Springer, 2021. — 293 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN: 978-3-030-66518-0.This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time applications. This book introduces a broad range of topics in deep learning. The authors start with the fundamentals, architectures, tools needed for effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python. They proceed with advanced concepts with hands-on sessions for deep learning. Engineers, scientists, researches looking for a practical approach to deep learning will enjoy this book.Introduction to Deep Learning
Deep Learning Applications with Python
Deep Learning for Character Recognition
Keras and TensorFlow: A Hands-On Experience
Deploying Deep Learning Models for Various Real-Time Applications Using Keras
Advanced Deep Learning Techniques
Potential Applications of Deep Learning in Bioinformatics Big Data Analysis
Dynamic Mapping and Visualizing Dengue Incidences in Malaysia Using Machine Learning Techniques
Vector-Borne Disease Outbreak Prediction Using Machine Learning Techniques
Eukaryotic Plasma Cholesterol Prediction from Human GPCRs Using K-Means with Support Vector Machine
A Survey on Techniques for Early Detection of Diabetic Retinopathy