Use this thread to share your work from this week.
The best way to structure your reply is to include:
Read the getting started post to understand what you can post:
https://jovian.ai/forum/t/share-your-work-getting-started/7166/2
I completed the classification of Fruits360 dataset on Kaggle using
Feedforward and Convolution Neural Network.
I even tried ResNet 9. Check it out !
Hi there!
I finally finished my blogpost, and I am ready to share it with You guys!
I tried a slightly different approach, my aim wasn’t building the greatest classifier, but just playing with the deep learning technique.
I hope You’ll like it.
Best wishes,
Attila
Hey everyone,
This is my Final Course Project : Face-Mask-Detection using PyTorch
Here’s the link to the github repository: https://github.com/Rahul0128/Face-Mask-Detection-Pytorch
And the link to my blog: https://medium.com/@rahulpillai0128/face-mask-detection-using-pytorch-c0761f578009
Dear all, I have used the ResNet9 in order to classify the Flowers with data augmentation like we did at the lecture. Please check my notebook and I am waiting for your feedbacks, thanks!
This is nice , Well I would suggest try applying resnet18 or resnet34 and apply model.freeze() and unfreeze function as in lectures to check if the accuracy improves or not …
I tried to classify garbage using PyTorch. It would be great if you have a look and give suggestions:
https://www.kaggle.com/aadhavvignesh/95-accuracy-pytorch-garbage-classification