This repository contains educational materials and tutorials that were developed while tutoring Machine Learning concepts to CS Lin. These resources provide a practical approach to learning ML/DS
- Optimization and gradient descent without pytorch (colab)
- Logistic regression and neural networks (colab)
- Logistic regression as a image segmentator (colab)
- Basics about PyTorch (colab)
- MNIST classifier (colab)
- metrics: accuracy, precision, recall and AUROC (colab)
- Intro: torch lightning (colab)
- Convolutional neural networks (colab)
- Image segmentation: Metrics and losses(slides)
- network_blocks(slides)
Why don't you do your best?
