1. PyTorch Basics
2. Linear Regression
3. Logistic Regression
4. Artificial Neural Networks
5. Convolutional Neural Networks
6. Recurrent Neural Networks
7. LSTM
8. GPU

The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning.

The MNIST database contains 60,000 training images and 10,000 testing images.

The CIFAR-10 dataset is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. The 10 different classes represent airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks. There are 6,000 images of each class

• Logistic Regression
• Artificial Neural Networks
• Convolutional Neural Networks
• PyTorch with GPU

• CNN
• RNNN
• LSTM
• GPU