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.
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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.
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Lecture 5 | Convolutional Neural Network
History and Modern in CNN and its operations.
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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)