Syllabus Deep Learning Principles and Practices (3174201) Unit No. Content 1. Introduction Deep learning basics, Applications : Discuss in detail, Challenges, Neural Network concepts (Chapter - 1) 2. Neural Network Definition, Introduction of Neural Network, Working of Neural Network, Types of Neural Networks, Activation function, Deep Feed forward Network, Neural Network - Use Case, Applications of ANN, ANN vs BNN. (Chapter - 2) 3. Neural Network Based Fuzzy Systems Neural Realization of Basic Fuzzy Logic Operators, Neural Network Based Fuzzy Logic Inference, Neural Network Driven Fuzzy Reasoning, Rule based Neural Fuzzy Modeling, Neural Fuzzy Relational Systems, Neuro Fuzzy Controllers, Recent Applications. (Chapter - 3) 4. Introduction to Tensorflow, Tenserflow Basics, Transfer Learning, Optimization in Deep Learning, Natural Language Processing basics. (Chapter - 4) 5. Deep Learning Algorithms : CNN, LSTM, RNN, GAN, RBFN, MLP, SOM, DBN, RBM. (Chapter - 5)
