A game theoretic approach to explain the output of any machine learning model.
- interpretability
- machine-learning
- deep-learning
- gradient-boosting
47,133 repositories indexed
1–24 of 120 · Most stars
A game theoretic approach to explain the output of any machine learning model.
StableLM: Stability AI Language Models
This repository contains implementations and illustrative code to accompany DeepMind publications
Kubernetes Community Documentation
A scikit-learn compatible neural network library that wraps PyTorch
Create delightful software with Jupyter Notebooks
Debugging, monitoring and visualization for Python Machine Learning and Data Science
MIMIC Code Repository: Code shared by the research community for the MIMIC family of databases
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Algorithms for outlier, adversarial and drift detection
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Python Productivity for ZYNQ
Providing the solutions for high-frequency trading (HFT) strategies using data science approaches (Machine Learning) on Full Orderbook Tick Data.
Implementing a Neural Network from Scratch
Handout for the tutorial "Creating publication-quality figures with matplotlib"
Synthetic data generators for tabular and time-series data
Koç University deep learning framework.
ProtTrans is providing state of the art pretrained language models for proteins. ProtTrans was trained on thousands of GPUs from Summit and hundreds of Google TPUs using Transformers Models.
Detecting Text in Natural Image with Connectionist Text Proposal Network (ECCV'16)
Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics
A Deep Learning Toolkit for DTI, Drug Property, PPI, DDI, Protein Function Prediction (Bioinformatics)
CatBoost tutorials repository
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
Utility functions for handling MIDI data in a nice/intuitive way.