Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
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Updated
Apr 29, 2024 - Python
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Better GitHub statistics images for your profile, with stats from private repos too
Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
InterpretDL: Interpretation of Deep Learning Models,基于『飞桨』的模型可解释性算法库。
Multiplex: visualizations that tell stories—A Python library to create and annotate beautiful network graph visualizations, text visualizations and more.
Magic to display dynamic call graphs of Python function calls
Python implementation for TSP using Genetic Algorithms, Simulated Annealing, PSO (Particle Swarm Optimization), Dynamic Programming, Brute Force, Greedy and Divide and Conquer
Visualizations of Mittelmann benchmarks
Python API for reading and manipulating polygon data of Electronic Navigational Charts (ENC)
Fantasy Premier League Stats, Visualizations & Analysis. ⚽ 📊 📈
Generate daily updated customizable visualizations of user and repository statistics from the GitHub GraphQL and REST APIs using GitHub Actions and Secrets
The project I made for the Atlassian Hack@Home challenge's final 4-hour individual hackathon where I won the 1st Prize from an initial pool of more than 2,000 students.
Generates the GitHub statistics for my profile
Code for the paper " Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations"
One stop-shop for matplotlib based visualizations
IonTorrent variant reporting pipeline for clinical interpretation of cancer panel results
Analysis of a cities dataset with 3 algorithms: K-means, K-medoids, and Bottom-Up Hierarchical Clustering
More practical use of Twint with ES and Kibana.
Extensions to kubeflow pipeline sdk.
This is a helper package for pandas, visualizations and scikit-learn
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