Syllabus
Introduction to Neural network and Back propagation-Basics of Tensor flow and Keras-Details on Convolutional Neural Networks and types of different convolutions-recent topics in Recurrent Neural Net-works, LSTM, GRUs-Time series Processing-Details of Transformer Networks for text and Vision- Instance and Semantic Segmentation-Generative Models, VAE-Deep Generative Adversarial Networks- Model Interpretation etc.
Text Books
Same as Reference
References
1. Deep Learning, Ian Good fellow, Yoshua Bengio and Aaron Courville, ISBN-13:978- 0262035613, MIT Press, 2016.
2. Recent peer reviewed journals and conferences.