cs231n-notes

This repository contains the notes from Stanford CS231N course. Link to youtube lecture

Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition

Brief introduction to the history of Computer Vision, Deep Learning and the problems to tackle in Computer Vision.
Link to my Note

Lecture 2 | Image Classification Pipelines

Introduction to the image classification pipelines and train a simple model for image classification.
Link to my Note

Lecture 3 | Loss Function and Optimization

Introduction to hinge loss, softmax function and optimization.
Link to my Note

Lecture 4 | Backpropagation and Neural Network

Introduction to Neural Network backpropagation flow, equations and intuiation.
Link to my Note

Lecture 5 | Convolutional Neural Network

History and Modern in CNN and its operations. Link to my Note

Lecture 6 | Training Neural Network 1

Basic Training Procedure hyperparameters optimization. Link to my Note

Lecture 7 | Training Neural Network 2

[Link to my Note](Day7_Training_Neural_Network_2.md)