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A list of useful payloads and bypass for Web Application Security and Pentest/CTF
- pentest
- payload
- bypass
- web-application
TranslatedHand-written implementations of all the algorithms in Li Hang's book "Statistical Learning Methods" (《统计学习方法》)
- machine-learning-algorithms
- code
- statistical-learning-method
DeFi Developer roadmap is a curated Developer handbook which includes a list of the best tools for DApps development, resources and references!
A collection of important graph embedding, classification and representation learning papers with implementations.
- graph2vec
- classification-algorithm
- graph-kernels
- weisfeiler-lehman
A Collection of Vulnerabilities in ERC20 Smart Contracts With Tokens Affected
- smart-contracts
- erc20-tokens
- vulnerabilities
- solidity
zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
- machine-learning
- python
- evolutionary-algorithms
- genetic-algorithm
Evidence archive for Jesus of Nazareth: research dossier (PDF), New Testament, gnostic and extracanonical gospels, church fathers, ancient witnesses, Roman legal documents, archaeology, and all 238 cited references — searchable reader at https://sybil-solutions.github.io/all-historical-evidence-of-jesus-christ/
Companion repository for “In-Context Learning for Robots: Methods and Applications” — methods, datasets, and benchmarks organized by taxonomy and release date.
- awesome-list
- embodied-ai
- imitation-learning
- in-context-learning
Bringing thousands of learners together to unpack DeepInfer through peer-reviewed explanations, documentation, and hands-on examples.
End-to-end DevOps TaskFlow API — FastAPI, PostgreSQL, SQLAlchemy, Alembic, Docker Compose, Pytest and GitHub Actions CI,Kubernetes,prometheus,Grafana,helm,k9s,kompose,minikube,helmify
- alembic
- docker
- docker-compose
- fastapi
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette