Chapter 1: Introduction to NLP and Deep Learning Chapter Goal: Introduction of Deep Learning and NLP concepts, explanation of the evolution of deep learning and comparison of deep learning with other machine learning techniques in Python No of pages: 50-60 Sub -Topics 1. Deep Learning Framework - An overview 2. Comparison with other machine learning techniques 3. Why Python for Deep Learning 4. Deep Learning Libraries 5. NLP- An overview 6. Introduction to Deep Learning for NLP Chapter 2: Word Vector representations Chapter Goal: Introduction of basic and advanced word vector representation No of pages: 50-60 Sub - Topics 1. Overview of Simple Word Vector representations: word2vec, Glove 2. Advanced word vector representations: Word Representations via Global Context and Multiple Word Prototypes 3. Evaluation methods for unsupervised word embedding Chapter 3: Neural Networks and Back Propagation Chapter Goal: Neural Networks for named entity recognition No of pages: 50-60 Sub - Topics: 1. Learning Representations by back propagating the errors 2. Gradient checks, over-fitting, regularization, activation functions Chapter 4: Recurrent neural networks, GRU, LSTM, CNN Chapter Goal: Deep Learning architectures like RNN, CNN, LSTM, and CNN in great details with proper examples of each No of pages: 70-80 Sub - Topics: 1. Recurrent neural network based language model 2. Introduction of GRU and LSTM 3. Recurrent neural networks for different tasks 4. CNN for object identification Chapter 5: Developing a Chatbot Chapter Goal: Chatbots are artificial intelligence systems that we interact with via text or voice interface. Our aim is to develop and deploy a Facebook messenger Chatbot. No of pages: 50-60 Sub - Topics: 1. Development of a simple closed context Chatbot 2. Deployment using free server Heroku 3. Integrating Seq2seq model with the Chatbot 4. Integrating Image Identification model with the Chatbot Chapter 6: Interaction of Reinforcement Learning and Chatbot Chapter Goal: Detailed explanation of the Reinforcement Learning concept and one of the prevalent case studies/research paper on Reinforcement Learning applications for Chatbot No of pages: 20-30 Sub - Topics: 1. Introduction to Reinforcement Learning 2. Present applications of Reinforcement Learning for Chatbot 3. Detailed explanation of one of the research papers on applications of Reinforcement Learning for Chatbot schovat popis