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Resources for students in the Udacity's Machine Learning Engineer Nanodegree to work through Stanford's Convolutional Neural Networks for Visual Recognition course (CS231n).
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| 2026-08-05 | 260 |
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# Convolutional Neural Networks for Visual Recognition Resources for students in the [Udacity's Machine Learning Engineer Nanodegree](https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009) to work through Stanford's Convolutional Neural Networks for Visual Recognition course. ## Course Materials - [Course](http://cs231n.stanford.edu/) - [Assignments and Notes](http://cs231n.github.io/) - [Lecture Slides](http://cs231n.stanford.edu/syllabus.html) - [Lectures Videos](https://www.youtube.com/playlist?list=PLLvH2FwAQhnpj1WEB-jHmPuUeQ8mX-XXG) - [Reddit Channel](https://www.reddit.com/r/cs231n/) - [Twitter](https://twitter.com/cs231n) ## Helpful Resources [Andrej Karpathy's blog](http://karpathy.github.io/) [Andrew Trask's blog](http://iamtrask.github.io/) [Christopher Olah's blog on Neural Networks](http://colah.github.io/) [Convolutional neural networks](http://cthorey.github.io./backprop_conv/) [Backpropagation and batchnorm regularization ](http://cthorey.github.io./backpropagation/) [How Convolutional Neural Networks Work](http://brohrer.github.io/how_convolutional_neural_networks_work.html) [Make Your Own Neural Network](https://github.com/makeyourownneuralnetwork/makeyourownneuralnetwork) ## Student Solutions A place for students to share code, double check their work and troubleshoot problems. __Honor Code__ We ask that you not look at this section __unless you have finished the assignment or have spent quality time figuring out the problem.__ Out of respect for Stanford releasing their class to the public, please do not abuse this policy. Try your best to figure out the solutions on your own, read the Reddit forms, or ask questions on our Slack channel before looking at solution code. Personally, I like to spend a few days trying to figure something out before looking at solution code. __Contributions__ If you have finished the assignment, we hope you can add your answers to the repository for other students. If you choose to do so, please fork the repo and add a folder with your alias and put the assignments inside your folder. Always do a git pull before you do a git push so that there are no merge conflicts ``` git clone https://github.com/machinelearningnanodegree/stanford-cs231.git cd stanford-cs231/solutions mkdir yourdirectoryname Copy the assignment1 into yourdirectoryname cd /stanford-cs231/ cp -R /stanford-cs231/assignments/assignment1 /stanford-cs231/solutions/yourdirectoryname/assignment1 If there is no directory called assignment1 in your directory it will be automatically created with above Download the dataset by: cd yourdirectoryname/assignment1/cs231n/datasets run ./get_datasets.sh inside the datasets directory After everything is downloaded cd into the assignment1 directory backwards and then run ipython notebook ``` ======= > __Thanks to Contributors:__ [kvn219](https://github.com/kvn219), [LevinJ](https://github.com/LevinJ), [pranayaryal](https://github.com/pranayaryal), & [vijendra-rana](https://github.com/vijendra-rana)
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