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6 REIMAGINING WHAT'S NEXT m achine Comprehension is a very interesting but challenging task in both Natural Language Processing (NLP) and artificial intelligent (AI) research. There are several approaches to natural language processing tasks. With recent breakthroughs in deep-learning algorithms, hardware and user- friendly application programming interfaces (APIs) such as TensorFlow*, some tasks have become feasible up to a certain accuracy. This article contains information about TensorFlow implementations of various deep-learning models, with a focus on problems in natural language processing. The purpose of this project article is to help the machine to understand the meaning of sentences, which improves the efficiency of machine translation, and to interact with the computing systems to obtain useful information from it. Figure 1: A basic model of NLP using deep learning. Deep Learning for naturaL Language processing Rajat Sharma Intel® Green Belt Software Developer