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Udacity Deep Learning Nanodegree Projects

These are my five projects implemented during the Udacity Deep Learning Nanodegree Program.
Course completion link here

1. Predicting Bike-Sharing Data

In this project, a neural network from scratch ia built 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
The notebook link here
Model prediction on the test dataset was:

2. Convolutional Neural Network (CNN) project

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.
Note book link here
Model prediction on the human and dog images is:

3. Generate TV Scripts

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.
Note book link here
TV sripts generated by the model:

4.Face Generation

In this project, I used generative adversarial networks (GANs) to generate new images of faces.
Notebook link here
Face generated by the model

5. SageMaker deployment project (AWS SageMaker)

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.
Notebook link here