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A game theoretic approach to explain the output of any machine learning model.
- interpretability
- machine-learning
- deep-learning
- gradient-boosting
stable diffusion webui colab
- stable-diffusion
- stable-diffusion-web-ui
- stable-diffusion-webui
- colab
A scikit-learn compatible neural network library that wraps PyTorch
Debugging, monitoring and visualization for Python Machine Learning and Data Science
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Algorithms for outlier, adversarial and drift detection
- anomaly
- outlier
- concept-drift
- detection
ZeroCostDL4Mic: A Google Colab based no-cost toolbox to explore Deep-Learning in Microscopy
🍇 GRAPE is a Rust/Python Graph Representation Learning library for Predictions and Evaluations
- graph
- high-performance
- machine-learning
- knowledge-graph
Python package for Bayesian Machine Learning with scikit-learn API
- python
- bayesian-machine-learning
- machine-learning
- scikit-learn
Full tutorial of computer vision and machine learning basics with OpenCV and Keras in Python.
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
- feature-selection
- data-science
- python
Reference mapping for single-cell genomics
- single-cell
- deep-learning
- rna-seq-analysis
- data-integration
TranslatedLearning machine learning and quantitative analysis, in progress
Deep Reinforcement Learning for de-novo Drug Design
- deeplearning
- reinforcement-learning
- cheminformatics
- molecular-modeling
Tensorflow implementation of "Learning Deep Features for Discriminative Localization"
Fusing Histology and Genomics via Deep Learning - IEEE TMI
- pathomic
- fusion
- multimodal
- pathology
An OCaml kernel for Jupyter (IPython) notebook
- ocaml
- functional-programming
- jupyter-kernels
- machine-learning
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Pan-Cancer Integrative Histology-Genomic Analysis via Multimodal Deep Learning - Cancer Cell
- histology
- wsi-images
- pan-cancer-analysis
- genomics
Materials for GWU DNSC 6279 and DNSC 6290.
Python for chemoinformatics
- chemoinformatics
- scikit-learn
- cheminformatics
- python
scikit-learn wrappers for Python fastText.
Usiigaci: stain-free cell tracking in phase contrast microscopy enabled by supervised machine learning
- tensorflow
- python3
- keras
- resnet-101