Deep Learning with R

Abhijit Ghatak is a Data Scientist and holds an M.E. in Engineering and M.S. in Data Science from Stevens Institute of Technology, USA. He began his career as a submarine engineer officer in the Indian Navy and worked on various data-intensive projects involving submarine operations and construction. Thereafter he has worked in academia, technology companies and as a research scientist in the area of Internet of Things (IoT) and pattern recognition for the European Union (EU). He has published several papers in the areas of engineering and machine learning and is currently a consultant in the area of machine learning and deep learning. His research interests include IoT, stream analytics and design of deep learning systems.

• Introduction to Machine Learning.- Introduction to Neural Networks .- Deep Neural Networks – I .- Initialization of Network Parameters.- Optimization.- Deep Neural Networks - II.- Convolutional Neural Networks (ConvNets).- Recurrent Neural Networks (RNN) or Sequence Models.- Epilogue.

“This is a very useful book in the domain of deep learning and the author has done a great job of bringing all the paradigms and libraries together to illustrate how they work for real big data. I am glad to have this book on my shelf.” (Anna Bartkowiak, ISCB News, Vol. 68, December, 2019)