Deep learning models are widely used in different fields due to its capability to handle large and complex datasets and produce the desired results with more accuracy at a greater speed. In Deep learning models, features are selected automatically through the iterative process wherein the model learns the features by going deep into the dataset and selects the features to be modeled. In the traditional models the features of the dataset needs to be specified in advance. The Deep Learning algorithms are derived from Artificial Neural Network concepts and it is a part of broader Machine Learning Models.
This book intends to provide an overview of Deep Learning models, its application in the areas of image recognition & classification, sentiment analysis, natural language processing, stock market prediction using R statistical software package, an open source software package.
The book also includes an introduction to python software package which is also open source software for the benefit of the users.
This books is a second book in series after the author’s first book- Machine Learning: An Overview with the Help of R Software
Editor
International Journal of Statistics and Medical Informatics
www.ijsmi.com/book.php
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