DeepLearning
cs231n
Our great sponsors
DeepLearning | cs231n | |
---|---|---|
1 | 1 | |
3 | 42 | |
- | - | |
0.0 | 0.0 | |
almost 2 years ago | over 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DeepLearning
-
Help with my PyTorch implementation of PPO
I implemented PPO using PyTorch here. As is suggested, I was trying it on very simple environment (CartPole-v1).
cs231n
-
Assignment solutions for Stanford CS231n-Spring 2021
Here's the link to my Repo.
What are some alternatives?
AI-For-Beginners - 12 Weeks, 24 Lessons, AI for All!
coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models
conformal_classification - Wrapper for a PyTorch classifier which allows it to output prediction sets. The sets are theoretically guaranteed to contain the true class with high probability (via conformal prediction).
stanford-cs229 - 🤖 Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford
analisis-numerico-computo-cientifico - Análisis numĂ©rico y cĂłmputo cientĂfico
Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.
Deep-Learning-Experiments - Videos, notes and experiments to understand deep learning
stanford-CS229 - Python solutions to the problem sets of Stanford's graduate course on Machine Learning, taught by Prof. Andrew Ng [UnavailableForLegalReasons - Repository access blocked]
weightless_NN_decompression - Proof of concept for neural network decompression without storing any weights
monodepth2 - [ICCV 2019] Monocular depth estimation from a single image
chainerrl - ChainerRL is a deep reinforcement learning library built on top of Chainer.
deep-learning-v2-pytorch - Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101