Final Project - Text Classification
Now that you have worked through the course exercises it is time for the final project. You will build a text classifier for classifying text into multiple categories.
Now that you have worked through the course exercises it is time for the final project. You will build a text classifier for classifying text into multiple categories.
The goal of the final image classification project is to train a convolutional neural network on a dataset of your choice. Kaggle is a nice platform where you can find big datasets that you can use for your project. Please share the link to the dataset you have used in your final submission.
Here are some datasets that you could use:
Cat and Dog images (2 classes):
CT Scans for COVID 19 (3 classes):
Food classification (35 classes
Flower Imge classification (102 classes):
Mushroom classification (215 classes)
Bird Image Classification (525 classes)
You can find more public datasets at Kaggle .
Your task is to download a dataset of your choice and the following notebook. The notebook contains the code for finetuning a pretrained convolutional neuran network with PyTorch. The code has already been written for you, so you only need to make this notebook run on your machine and answer the three questions in the notebook after you have trained the model.
When you have trained your model we expect you to send us the following artifacts:
The notebook with all the cell outputs after the training. You can export the notebook as an HTML document.
The model weights
The three questions in the notebook must be answered. You can write down the answers in the notebook.