This is a repo with links to everything you'd ever want to learn about data engineering
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This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
- hacking
- penetration-testing
- hacking-series
- cybersecurity
A game theoretic approach to explain the output of any machine learning model.
- interpretability
- machine-learning
- deep-learning
- gradient-boosting
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")
- prompt-engineering
- chatgpt
- deeplearning
- framework
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM 3, and Qwen3-VL.
Playing Pokemon Red with Reinforcement Learning
Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.
- tensorflow
- machine-learning
- regression
- convolutional-neural-networks
Build a modern LLM from scratch. Every line commented. Explained like we are five.
- attention-mechanism
- deep-learning
- educational
- from-scratch
OmniGen2: Exploration to Advanced Multimodal Generation. https://arxiv.org/abs/2506.18871
Debugging, monitoring and visualization for Python Machine Learning and Data Science
🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models
- python
- machine-learning
- explainability
- explainable-ml
The repository is about 100+ python programming exercise problem discussed, explained, and solved in different ways
- python
- programming
- learning-exercise
- python-programming-exercises
A library for debugging/inspecting machine learning classifiers and explaining their predictions
- scikit-learn
- machine-learning
- xgboost
- lightgbm
📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
- football
- xg
- expected-goals
- statsbomb
List of papers, code and experiments using deep learning for time series forecasting
- time-series-forecasting
- lstm-neural-networks
- lstm
- deep-learning
Face Depixelizer based on "PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models" repository.
Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX
- tensorflow
- onnx
- export
- convert
Coding the Machine Learning Tutorial for Learning to Learn
Những kiến thức cần thiết để học tốt Machine Learning trong vòng 2 tháng. Essential Knowledge for learning Machine Learning in two months.
- machine-learning
- tensorflow
- tensorflow-tutorials
- tensorflow-experiments
Explain, analyze, and visualize NLP language models. Ecco creates interactive visualizations directly in Jupyter notebooks explaining the behavior of Transformer-based language models (like GPT2, BERT, RoBERTA, T5, and T0).
- nlp
- visualization
- explorables
- natural-language-processing
The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
- quantum-algorithms
- quantum-software
- quantum-applications
- quantum-open-source
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
- deep-learning
- vision-transformer
- bert-model
- bert