The major theme of this chapter was generating text automatically using RNNs. We started the chapter with a discussion about language models and their applications in the real world. We then carried out an in-depth overview of recurrent neural networks and their suitability for language model tasks. The differences between traditional feedforward networks and RNNs were discussed to get a clearer understanding of RNNs. We then went on to discuss problems and solutions related to the exploding gradients and vanishing gradients experienced by RNNs. After acquiring a detailed theoretical foundation of RNNs, we went ahead with implementing a character-level language model with an RNN. We used Alice's Adventures in Wonderland as a text corpus input to train the RNN model and then generated a string as output. Finally, we discussed some ideas for improving our character...
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Dr. Sunil Kumar Chinnamgari has a Ph.D. in computer science and specializes in machine learning and natural language processing. He is an AI researcher with more than 14 years of industry experience. Currently, he works in the capacity of lead data scientist with a US financial giant. He has published several research papers in Scopus and IEEE journals and is a frequent speaker at various meetups. He is an avid coder and has won multiple hackathons. In his spare time, Sunil likes to teach, travel, and spend time with family.
Read more about Dr. Sunil Kumar Chinnamgari
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Dr. Sunil Kumar Chinnamgari has a Ph.D. in computer science and specializes in machine learning and natural language processing. He is an AI researcher with more than 14 years of industry experience. Currently, he works in the capacity of lead data scientist with a US financial giant. He has published several research papers in Scopus and IEEE journals and is a frequent speaker at various meetups. He is an avid coder and has won multiple hackathons. In his spare time, Sunil likes to teach, travel, and spend time with family.
Read more about Dr. Sunil Kumar Chinnamgari