🎓 Path to a free self-taught education in Computer Science!

A list of Reverse Engineering articles, books, and papers

Reverse engineering framework in Python

Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…

Source code and exercises from the book "Black Hat Python" by Justin Seitz.

Answers to 120 commonly asked data science interview questions.

[NeurIPS 2021] Well-tuned Simple Nets Excel on Tabular Datasets

Python ML pipeline that showcases mltrace functionality.

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Accurate and efficient Spiking recurrent networks on ECG,SHD,SSC,SOLI,(p)SMNIST,TIMIT

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

💨 Fast, Async-ready, Openapi, type hints based framework for building APIs

XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions

XGBoost Feature Interactions Reshaped

A collection of research papers on decision, classification and regression trees with implementations.

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

A Python package for modular causal inference analysis and model evaluations