Dataset : E2E NLG Challenge
Each instance consist of a dialogue act-based meaning representation (MR) and up to 5 references in natural language
MR:
name[The Eagle], eatType[coffee shop], food[French], priceRange[moderate], customerRating[3/5], area[riverside], kidsFriendly[yes], near[Burger King] NL:
Image detection is common task in computer vision.It is used in as a subtask for many important industrial application such as autonomous vehicle.
Augmented image data using transformation technique(random crop,vertical flip) Implemented and trained RESNET family of architecture for image detection with 86% accuracy
Named Entity Recognition is a method to locate and identify important concepts within documents. I trained vanilla and GRU variant of recurrent neural network to identify person,location and organization from sentences.
Language Understanding Capabilities of computers is crucial to many modern applications such as voice assistants,autocomplete suggestions for emails and answering questions by users in search engines.Out of them Reading Comprehension is an important and challenging problem.