Course Project - Zero to GANS

##Course Project - Train a Deep Learning Model from Scratch

In this project an attempt made to apply all the concepts learned in this course to train deep learning models end-to-end with PyTorch, and further experimenting with different hyperparameters & metrics to check the effect of selected parameters against model prediction with test data.

The steps followed in this project is outlined as:

1. Select a dataset online from https://www.kaggle.com/zalando-research/fashionmnist as per interest.
2. Clear description about the data is to be provided.
3. Clear description about the type of problem.
4. Clear description about the modeling objective.
   5.Cleaning of the data is required after checking and to perform exploratory analysis
5. Creating the “Model” followed by it’s training, and then evaluate against test dataset.
6. Saving of all type model data and metrics each time, and repeat the process with different parameters.
7. Finally checking of the model performance with different parameters by using “Compare” mode available in Jovian.

Submission Deadline: Jan 9, 2021 11:59 PM GMT

For the course project, picked a dataset of choice and applied the concepts learned in this course to train deep learning models end-to-end with PyTorch, experimenting with different hyperparameters & metrics.

Example notebooks for reference:

https://jovian.ai/aakashns/simple-cnn-starter

https://jovian.ai/aakashns/transfer-learning-pytorch

https://jovian.ai/aakashns/06b-anime-dcgan

https://jovian.ai/aakashns/05b-cifar10-resnet

I am planning to download the following databases and do project with one:

https://www.kaggle.com/zalando-research/fashionmnist

https://www.kaggle.com/alxmamaev/flowers-recognition

https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia

If all ok then fine.