Assignment 4 - Course Project

For the course project, you will pick any dataset of your choice and apply the concepts learned in this course to train deep learning models end-to-end with PyTorch, experimenting with different hyperparameters & metrics. You will prepare a project report in the form of a blog post to summarizing your results & findings (the blog post is mandatory).

Starter Notebook: There is no starter notebook for the project. Please use the “New Notebook” option from your Jovian profile to create a new notebook.

Guidelines for completing the project

  1. Find a dataset online (either download and existing dataset or create one from web scraping, Google images etc.)
  2. Understand and describe the modelling objective clearly
    1. What type of data is it? (images, text, audio etc.)
    2. What type of problem is it? (regression, classification, generative modelling, etc.)
  3. Exploratory data analysis - explore the data by plotting graphs and answer any questions you may have
  4. Modeling - try 4-5 approaches
    1. Define a model (network architecture)
    2. Pick some hyperparameters
    3. Train the model
    4. Make predictions on samples
    5. Evaluate on the test dataset
    6. Save the model weights
    7. Record the metrics
  5. Conclusions - summarize your learning & identify opportunities for future work
  6. Write a blog post to describe your experiments and summarize your work - this is the final submission. Use Github pages or Medium.

Notice:
More Details will be added soon