In this course you will learn about deep neural networks (deep learning), and how to leverage them in processing, understanding and mining for insights from text. We start with an introduction to neural networks and deep learning. We then dive into essentials of representation learning like word and document embeddings and then move onto more complex methodologies including convolutional neural networks and sequence models and deep transfer learning approaches including universal embeddings and transformers. Popular applications are also covered with hands-on tutorials and exercises including text classification, information extraction, recommenders, search, summarization, translation and more.
Mr. Dipanjan Sarkar
Dipanjan (DJ) Sarkar is a Data Science Lead, published author and has been recognized as a Google Developer Expert in Machine Learning by Google in 2019. He has also been recognized as one of the Top Ten Data Scientists in India, 2020 by a few leading technology magazines and publishing houses. Dipanjan has led advanced analytics initiatives working with several Fortune 500 companies like Applied Materials, Intel and Open Source organizations like Red Hat (now IBM). He primarily works on leveraging data science, machine learning and deep learning to build large- scale intelligent systems.
He holds a master of technology degree from IIIT Ban...