This project was developed in order to detect whether a patient has pneumonia or not from a chest x-ray image. In addition to this, it is deployed on the web using Flask.

NER is a method of extracting the relevant information from a large corpus and classifying hose entities into predefined categories such as location, organization, name and so on.

Visual Question Answering(VQA) is a system that takes an image and natural l anguage question about the image as an input and generates natural language answer as an output .

Given a review from various products of amazon to determine whether the review is positive or negative.

Given the above various set of features, the aim is to predict the transaction price of the house.

Building the model on the environmental and seasonal conditions to analyze their influence on bike rental count.

Building a deep learning model that takes an image as the input and detects objects in mages and localizes it with the help of bounding boxes. Also deployed it using Flask on the local server.

Prediction of flight ticket price given various features like route, source, destination, etc.