AI-Med | Educational Content

Educational Content for Deep Learning

Learning basics of Machine learning
1. Numpy and linear algebra
Notebook Exercise

numpy excersices
2. Pandas
Notebook Exercise

pandas excersices
3. Matplotlib
Notebook Exercise

matplotlib excersices
4. Statistics
Notebook Exercise

statistics excersices
5. Image processing
Notebook Exercise

Image processing excersices
6. Tricks in Numpy
Notebook Exercise

Tricky actions numpy could provide
7. ML Theoretical Basics
Notebook Exercise

Linear Regression, Logistic Regression, Backpropagation, CNNs, RNNs, Generative Models
8. Introduction to Pytorch
Notebook Exercise

an Introduction of how to use Pytorch
Learning Tasks
1. Classification with Fully Connected Neural Networks
Notebook Exercise

MNIST classification with a fully connected model
2. Classification with Convolutional Neural Networks
Notebook Exercise

CIFAR10 classification with a convolutional model
3. Classification with Transfer Learning
Notebook Exercise

CIFAR10 classification with transfer learning on Inception V3
4. Clustering using pretrained deep models
Notebook Exercise

MNIST clustering using pretrained ResNet 18 and KMeans
5. Image Captioning
Notebook Exercise

Image captioning using CNNs for understanding the image, and LSTM for generating a caption
6. Conditional GAN
Notebook Exercise

Generating right half of an MNIST digit given the left half.