Nitarshan's starred repositories
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
vim-galore
:mortar_board: All things Vim!
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
digital_video_introduction
A hands-on introduction to video technology: image, video, codec (av1, vp9, h265) and more (ffmpeg encoding). Translations: 🇺🇸 🇨🇳 🇯🇵 🇮🇹 🇰🇷 🇷🇺 🇧🇷 🇪🇸
easy-application
Over 400 software engineering companies that are easy to apply to
DCGAN-tensorflow
A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"
tensorflow_tutorials
From the basics to slightly more interesting applications of Tensorflow
DeepLearningTutorials
Deep Learning Tutorial notes and code. See the wiki for more info.
dcgan_code
Deep Convolutional Generative Adversarial Networks
neural-storyteller
A recurrent neural network for generating little stories about images
orly-full-res
Full resolution images of the O RLY book covers made by The Practical Dev
Bayesian-Modelling-in-Python
A python tutorial on bayesian modeling techniques (PyMC3)
deep-rl-tensorflow
TensorFlow implementation of Deep Reinforcement Learning papers
neal-react
Startup Landing Page Components for React.js
sketch-rnn
Multilayer LSTM and Mixture Density Network for modelling path-level SVG Vector Graphics data in TensorFlow
kaggle-galaxies
Winning solution for the Galaxy Challenge on Kaggle (http://www.kaggle.com/c/galaxy-zoo-the-galaxy-challenge)
learning-to-communicate
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
summerschool2015
Slides and exercises for the Deep Learning Summer School 2015 programming tutorials