Lists (9)
Cyber Security
Cyber security related6 repositories
Future stack
Interesting tools on my to-use-list, mostly Rust related.16 repositories
GAMs
Generalized Additive Models, mostly RStats9 repositories
Image processing
DL,ML with a focus on segmentation and other image models41 repositories
Lectures and Notes
TLDR-like notes and other awesome lists31 repositories
Likes
Tools I do not often use but like due to the implementation, results, vision behind, or code beauty.95 repositories
Model-related
Tools to make model diagnostics/interpretation easier33 repositories
🚀 My stack
27 repositories
Starred repositories
33
stars
written in Jupyter Notebook
Clear filter
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
Python Data Science Handbook: full text in Jupyter Notebooks
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
Public facing notes page
Implementations from the free course Deep Reinforcement Learning with Tensorflow and PyTorch
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
Tutorials and training material for the H2O Machine Learning Platform
Code for the Lovász-Softmax loss (CVPR 2018)
Text and supporting code for Modeling and Simulation in Python
Bayesian learning and inference for state space models
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy
A few notebooks about deep learning in pytorch
A python package that includes many methods for decoding neural activity
High-quality Neural Networks for Computer Vision 😎
add statistical annotations (pvalue significance) on an existing boxplot generated by seaborn boxplot
Keras implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. (https://arxiv.org/abs/1810.11654).
Generic U-Net Tensorflow 2 implementation for semantic segmentation
Lecture materials "Bio-image analysis, biostatistics, programming and machine learning for computational biology" at the Center of Molecular and Cellular Bioengineering (CMCB) / University of Techn…
Introduction to Numpy and Pandas
Implementations of computer vision concepts.
Notebooks on fitting mixed-effects models in Julia
Course material for fundamentals in digital image processing
Python scripts for data set preparation and CNN training/inference
Repository supporting the paper titled "Interpretable Deep Learning Systems for Multi-Class Segmentation and Classification of Non-Melanoma Skin Cancer"
Content for Biomedical Imaging Analysis 4