links#
frameworks#
https://openml.org/ open platform for sharing datasets, algorithms, and experiments
https://www.kaggle.com/ - Kaggle
Deep explanations#
https://theaisummer.com/ - read about deep learning
https://explained.ai/ - Deep explanations
https://udlbook.github.io/udlbook/ - Understanding Deep Learning
https://www.bishopbook.com/ - comprehensive introduction to the central ideas
https://www.deeplearningbook.org/ - mit Press book repo
https://d2l.ai/chapter_convolutional-modern/index.html - architectures
concepts#
https://nhigham.com/index-of-what-is-articles/ - What is …?
math#
https://www.matrixcalculus.org/ - derivative calculator
visualization#
dair-ai/ml-visuals - presentation figures
https://www.data-to-viz.com/ - visualization data
lilipads/gradient_descent_viz - gradient descent visualization
ashishpatel26/Tools-to-Design-or-Visualize-Architecture-of-Neural-Network - tools repo
https://alexlenail.me/NN-SVG/ - NN-architecture schematics
LucaBonfiglioli/nnviz - visualize neural networks
johnmarktaylor91/torchlens - TorchLens visualization
lutzroeder/Netron - viewer for neural network
https://arxiv.org/abs/1311.2901 - Feature Visualization
blogs#
https://dm13450.github.io/blog/ - Markwick blog
https://lilianweng.github.io/ - Lil’Log blog
https://lernapparat.de/statistics-deep-learning-nonparametric
books#
gimac/gninrael-enihcam - collection repo
christianversloot/machine-learning-articles - articles repo
articles#
https://scribe.rip/4e79bd3b1b54 - memory access perspective on GPUs
https://scribe.rip/841dba49df5e - Explanation of the Dimensions in CNN
https://scribe.rip/ee40425aea1f - resnext
https://scribe.rip/92941c5bfb95 - EfficientNet
https://www.jeremyjordan.me/semantic-segmentation/ - semantic segmentation
https://scribe.rip/3f330efe697b - Average Precision
feature tools#
deep#
KindXiaoming/pykan - Kolmogorov-Arnold (KAN) Networks
Torch#
davidstutz/torch-examples - Torch Examples
https://torchdrift.org/ - drift detection for PyTorch
qubvel-org/segmentation_models.pytorch - segmentation models in PyTorch
pytorch/captum - model interpretability
#
https://optuna.org/ - A hyperparameter optimization framework
https://www.nltk.org/ - embedding
ddbourgin/numpy-ml - collection of machine learning algorithms implemented exclusively in NumPy
training#
https://www.deeplearning.ai/short-courses/ - short courses
https://d2l.ai/ - Dive into Deep Learning
cv#
https://lilianweng.github.io/posts/2017-10-29-object-recognition-part-1/
https://lilianweng.github.io/posts/2017-12-15-object-recognition-part-2/
https://lilianweng.github.io/posts/2017-12-31-object-recognition-part-3/
https://lilianweng.github.io/posts/2018-12-27-object-recognition-part-4/
math#
mitmath/matrixcalc - MIT Matrix Calculus for Machine Learning 18.S096
https://mml-book.github.io/ - (mmlBook) Mathematics for Machine Learning
https://mixtape.scunning.com/ - Mixtape: Explaining the Mathematics of Machine Learning
srush/Tensor-Puzzles - Tensor Puzzles