For FinTechs that lend to households and firms, correctly predicting whether or not a loan will be a default is very important. In this project, using the historical data from 2007 to 2018, we build a deep learning model to predict the chance of default for future loans using the historical data. Benchmark models include logistic models, decision trees or random forests.

Self-driving cars are the future as people can entirely depend on the car for traveling.

In the world of AI, many researchers and big companies like Tesla, Google, Mercedes-Benz, Toyota, Ford, and Audi are working on self-driving vehicles and cars. To achieve accuracy with this technology, vehicles need to understand and follow the traffic rules accordingly.

There are many types of traffic signs, such as no parking, speed limit, no-entry, turn left or right, school ahead, no honking, and so on.

We create a model that can accurately distinguish between distinct traffic signals from photos using a Convolutional Neural Network.

Artificial Intelligence has evolved fast over the last years and is currently able to solve problems that are very complex and require human specialization.

A lot of research happens every day to use deep learning for the betterment of humanity, and one such example is healthcare. We build a model using a convolutional neural network that can classify lung infection in a person using medical imagery.