computer-vision

Why we included this project

For anyone self-teaching deep learning, this repository bundles the Stanford CS231n lecture materials with three complete programming assignments that progress from kNN and SVM classifiers to two-layer networks and finally to training and fine-tuning deep CNNs on ImageNet. The notebooks are ready to run and modify on your own machine, so you can experiment with loss functions, optimization, and fine-tuning without needing to set up a full course environment. The lecture index is also handy for quick refreshers on topics like batch normalization or recurrent architectures. Because the code follows the structure of the classic CS231n assignments, it makes a useful starting point when you're building your own image classification pipelines.