Done with all the assignments, now, will be participating in my first Kaggle competition(although it's not open to everyone still there will be a lot of competition from the participants of this course) and will start working on the course project.
Learned about different hyperparameter tuning, activation functions and we trained a model using image classification to do classification of images of everyday objects using neural networks.
Dataset used: CIFAR-10
Accuracy achieved: 55% to 56%
My key observations🧐 during this assignment are mentioned in the compare tab here Have a look at it, especially the Version-9 which contains a random selection of activation functions selected JUST FOR FUN🤪.
To find out what I have been doing in this Lock-down period, click here