So, I've been trying to learn Machine Learning. It's been an open subject for me for years; I remember going to university to learn computer science (which took me a long time to begin with -- a story for another day perhaps) already with the fuzzy idea of going into Machine Learning.
Prior to that I had studied Literature/Linguistics, and already I had the fuzzy idea there of specializing in Neurolinguistics. In the end I only did some introductory subjects on the matter before dropping out. Dropping out is sort of what I do, by the way. I'm trying to change this aspect of my personality, and actually starting this blog has to do with that.
Anyway, I've always been interested in ML, but for several years now I've been content with reading Wikipedia on it from time to time. And to sit back and sort of spectate about how the field has been advancing. Only a month ago I decided to get into it more seriously, and I've been doing the well-rated (and by now sort of classic) Coursera course on the matter (Andrew Ng's). It's been great fun, and I intend to do it to completion (not to drop out this time). What comes after that, I'm not completely sure right now, but that's sort of exciting on its own right.
Tools for learning machine learning. Obviously, this will expand into many files once I've developed more knowledge.
https://github.com/NathanUA/U-2-Net salient object detection https://github.com/pliang279/awesome-multimodal-ml reading about multimodal ml
https://github.com/fzenke/spytorch gradient learning for spiking neural networks
The case for sparsity in neural networks, Part 1: Pruning tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API https://stites.io/ -- great writing on neural networks Darknet: Open Source Neural Networks in C A Recipe for Training Neural Networks Towards understanding glasses with graph neural networks | DeepMind Neural networks and deep learning https://machinelearningmastery.com/learn-add-numbers-seq2seq-recurrent-neural-networks/ https://www.reddit.com/r/MachineLearning/comments/6l2esd/d_why_cant_you_guys_comment_your_fucking_code/ Meet The Stanford AI Lab Alums That Raised $15 Million To Optimize Machine Learning [P] I trained a GAN to generate photorealistic fake penises - MachineLearni h2oai/h2o-3: Open Source Fast Scalable Machine Learning Platform For Smarte https://www.forbes.com/sites/igorbosilkovski/2020/07/14/meet-the-stanford-ai-lab-alums-that-raised-15-million-to-optimize-machine-learning/amp/?__twitter_impression=true book by rahul khanna gpt 3 https://www.reddit.com/r/MachineLearning/comments/i1aafb/p_i_trained_a_gan_to_generate_photorealistic_fake/ fun with generating gans http://blog.ezyang.com/2013/01/nlp-the-missing-framework/ https://minimaxir.com/2019/09/howto-gpt2/ -- fun gpt 2 training time https://ezyang.github.io/convolution-visualizer/index.html https://www.reddit.com/r/MachineLearning/comments/gc834u/d_programming_language_choices_in_ai_nlp_and https://www.reddit.com/r/compsci/comments/g1eivp/from_cvpr_2020_turn_any_picture_to_a_3d_photo/ https://github.com/tokee/juxta https://www.reddit.com/r/compsci/comments/g8circ/a_repository_of_graph_classification_research/ https://arxiv.org/abs/2004.14545 https://arxiv.org/abs/2004.10934/
intels introductory ml course simple ml mindsweeper stream accel framework https://en.wikipedia.org/wiki/Discrete_cosine_transform <button class="pull-url" value="https://en.wikipedia.org/wiki/Discrete_cosine_transform">pull</button> signal processing: the discrete cosine transformation https://en.wikipedia.org/wiki/Discrete_cosine_transform <button class="pull-url" value="https://en.wikipedia.org/wiki/Discrete_cosine_transform">pull</button> data compression with fourier methods https://julialang.org/blog/2017/12/ml-pl/# https://www.youtube.com/watch?v=hx7kvTZLHYI https://www.youtube.com/watch?v=HgDdaMy8KNE whaaaat https://minimaxir.com/2019/09/howto-gpt2/ -- make text with gpt2! ml with cool functional languages https://www.youtube.com/watch?v=Jr9sptoLvJU&app=desktop
natural language processing
https://blog.benwiener.com/programming/2019/04/29/reinventing-the-wheel.html discovering optimal rolling shape in pytorch! https://minimaxir.com/2020/01/twitter-gpt2-bot/ https://github.com/alimir1/ml/blob/master/index.md framework for learning machine learning and self studying
A robust Python tool for text-based AI training and generation using GPT-2. Sharif Shameem on Twitter: "This is mind blowing. With GPT-3, I built a lay GPT-3 Creative Fiction · Gwern.net Giving GPT-3 a Turing Test A browser extension that displays the GPT-2 Log Probability of selected text Sharif Shameem on Twitter: &quot;This is mind blowing. With GPT-3, I built a lay
Making Anime Faces With StyleGAN · Gwern.net "TensorFlow Distributed Image Serving - A lightweight, RESTful remote inference library for decoupling deep learning development and deployment. Example usage cases with CycleGAN and Faster R-CNN. Includes tutorial ipynbs."
https://reddit.com/r/MachineLearning/comments/huyp4d/n_the_lisbon_ml_school_starts_tomorrow_talks_will https://www.reddit.com/r/learnmachinelearning/comments/hxxtik/ai_application_python_implementation_of_proximal/ https://www.reddit.com/r/magicTCG/comments/ht0o1f/oc_lands_painted_by_an_artificial_intelligence/ https://github.com/evhub/minecraft-deep-learning https://github.com/jasonmayes/Real-Time-Person-Removal https://github.com/facebookresearch/Hanabi_SPARTA https://github.com/OpenMined/PySyft https://github.com/koursaros-ai/nboost an automatic paper generator
https://github.com/evvo-labs/evvo distributed evolutionary algorithms nlp transformer model https://github.com/una-dinosauria/human-motion-prediction human motion prediction https://github.com/KartikChugh/Otto
End-to-End Object Detection with Transformers https://github.com/HumanCompatibleAI/evaluating-rewards https://github.com/paruby/snake-face Web Design semi-supervised learning architecture https://github.com/facebookresearch/dlrm deep learning recommendation model https://github.com/chiphuyen/machine-learning-systems-design machine learning systems design Neural Style Transfer for Fluids
eeg experiments in python and jupyter notebooks role2vec OpenAI Gym 'Lego style' pytorch deep learning model for CNNs latent adversarial generation of high resolution images gpt-3 open source driver assistance system, openpilot muzero paper gan work h2oai/h2o-3 Understanding LSTM Networks Artificial Intellgence Engines CS 330 Deep Multi-Task and Meta Learning mdroste/stata-pylearn: Supervised learning algorithms in Stata
Understanding LSTM Networks -- colah's blog jantic/DeOldify: A Deep Learning based project for colorizing and restoring https://openai.com/blog/image-gpt/ https://raw.githubusercontent.com/jethrokuan/braindump/master/org/actor_critic.org [actor-critic methods]]
EPR: The Strange Paradox of Distance and Observation | qnkxsovc Blog Explanation: Convolutions on Feature Maps With Multiple Channels | qnkxsovc Word2Vec Part 2: Color Vectors | qnkxsovc Blog Word Vectors, From the Ground Up | qnkxsovc Blog
Following learnopengl.com but my triangles being culled weirdly. Code in comments https://blogs.nvidia.com/blog/2020/05/22/gamegan-research-pacman-anniversary/ https://people.cs.umass.edu/~arjun/main/home/ https://jelv.is/
Full Stack Deep Learning boltzmann <button class="pull-url" value="https://en.m.wikipedia.org/wiki/Boltzmann_machine][boltzmann">pull</button> machine: recurrent neural networking neural networ chess engine https://github.com/alec-tschantz/predcoding predictive coding Programming Languages improving connectonomics https://news.ycombinator.com/item?id=23032243 openai jukebox: generative music styles<a href="/raw/garden/jakeisnt/file:music.org][Music"><img class="image-embed" src="/raw/garden/jakeisnt/file:music.org][Music"></img><p class="obsidian-embed"></a>⥅ Musiclt;/p> autoaugment: learning augmentation policices from data statistical distances and gan training
Amortized Population Gibbs Samplers with Neural Sufficient Statistics https://www.reddit.com/r/artificial/comments/gxrnhq/d_paper_explained_synthetic_petri_dish_a_novel/ https://towardsdatascience.com/the-unreasonable-ineffectiveness-of-deep-learning-on-tabular-data-fd784ea29c33 https://www.indexventures.com/perspectives/rebirth-robotics-how-covariant-unlocks-power-deep-learning-robots/ https://codeplay.com/ https://remis.io/ https://keras.io/examples/audio/speaker_recognition_using_cnn/ https://twitter.com/fchollet/status/1280733141980680193 <button class="pull-tweet" value=https://twitter.com/fchollet/status/1280733141980680193>pull</button> theriley106/isMask.py: Realtime Face Mask Detection in ~10 lines of Python Code
https://github.com/worldmodels/worldmodels.github.io models of the world?
https://oops.cs.columbia.edu/ predicting unintentional action in video
**Machine Learning, a subset of AI, uses computer algorithms to analyze data and make intelligent decisions based on what it has learned. **
Uses models not rules.
A solid reference I've used heavily is Models for machine learning from the IBM developer blog.
Machine Learning Models
The three types of machine learning