Description
Book SynopsisTable of ContentsChapter 1: Introduction to NLP and Deep LearningChapter 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 PythonNo of pages: 50-60Sub -Topics1. Deep Learning Framework - An overview2. Comparison with other machine learning techniques3. Why Python for Deep Learning4. Deep Learning Libraries5. NLP- An overview6. Introduction to Deep Learning for NLP
Chapter 2: Word Vector representationsChapter Goal: Introduction of basic and advanced word vector representationNo of pages: 50-60Sub - Topics 1. Overview of Simple Word Vector representations: word2vec, Glove2. Advanced word vector representations: Word Representations via Global Context and Multiple Word Prototypes3. Evaluation methods for unsupervised word embedding
Chapter 3: Neural Networks and Back Propagation Chapter Goal: Neural Networks for named entity recognitionNo of pages: 50-60Sub - Topics: 1. Learning Representations by back propagating the errors2. Gradient checks, over-fitting, regularization, activation functions
Chapter 4: Recurrent neural networks, GRU, LSTM, CNNChapter Goal: Deep Learning architectures like RNN, CNN, LSTM, and CNN in great details with proper examples of eachNo of pages: 70-80Sub - Topics: 1. Recurrent neural network based language model2. Introduction of GRU and LSTM3. Recurrent neural networks for different tasks4. CNN for object identification
Chapter 5: Developing a ChatbotChapter 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: 50-60Sub - Topics: 1. Development of a simple closed context Chatbot2. Deployment using free server “Heroku”3. Integrating Seq2seq model with the Chatbot4. Integrating Image Identification model with the ChatbotChapter 6: Interaction of Reinforcement Learning and ChatbotChapter Goal: Detailed explanation of the Reinforcement Learning concept and one of the prevalent case studies/research paper on Reinforcement Learning applications for ChatbotNo of pages: 20-30Sub - Topics: 1. Introduction to Reinforcement Learning2. Present applications of Reinforcement Learning for Chatbot3. Detailed explanation of one of the research papers on applications of Reinforcement Learning for Chatbot
