These are my five projects implemented during the Udacity Deep Learning Nanodegree Program.

In this project, I built a neural network from scratch to carry out a prediction problem on a Bike Sharing Dataset.

You can access the data set from here: Bike Sharing Dataset Data Set https://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset

In this project, I built a pipeline to process real-world, user-supplied images. Given an image of a dog, our algorithm will identify an estimate of the canine’s breed. If supplied an image of a human face, the code will identify the resembling dog breed.

In this project, I generated my own Seinfeld TV scripts using RNNs. I used a Seinfeld dataset of scripts from 9 seasons. The Neural Network I built generated a new, "fake" TV script.

In this project, I used generative adversarial networks (GANs) to generate new images of faces.

In this project, I constructed a recurrent neural network for the purpose of determining the sentiment of a movie review using the IMDB data set. I created this model using Amazon's SageMaker service. In addition, I deployed my model and construct a simple web app which interacts with the deployed model.