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Google Dork Cheatsheet

github.com

GitHub cheatsheet of Google dork operators and search patterns for finding exposed information.

Advances in Evolutionary Algorithms. Edited by: Witold Kosinski. ISBN 978-953-7619-11-4, PDF ISBN 978-953-51-5796-0, Published 2008-11-01.

Code for hyperparameter tuning/optimization of machine learning and deep learning algorithms.

All Secrets on a Single Page by Ivan Reznikov Nov, 2023 Towards AI.

Stanford research project that streams free over-the-air U.S. television channels while studying video-delivery algorithms.

Online learning algorithms (Perceptron, AROW, SCW, Logistic Regression).

Reinforcement Learning Coach by Intel® AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms.

A Python implementation of a number of popular recommendation algorithms for both implicit and explicit feedback.

Metric Learning Algorithms in Python.

Helps find, analyze or synthesize information for research and knowledge discovery.

OpenCV tool that combines image processing algorithms to remove black-bar caption filters from Snapchat images

Data Science at Home is a podcast about machine learning, artificial intelligence, and algorithms.

Efficient pure-Matlab implementations of graph algorithms to complement MatlabBGL's mex functions.

Graph layout algorithms in pure Julia.

A library for developing and comparing reinforcement learning algorithms (successor of [gym])(https://github.com/openai/gym).

Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained.

Helps teams build, deploy, observe or operate machine-learning systems.

Introduction to machine learning covering basic theory, algorithms and applications.

Algorithms for learning and inference with discrete probabilistic models.

About helping professional programmers confidently apply machine learning algorithms to address complex problems.

Open-source project that supports software development with code generation, analysis, debugging, or documentation.

A set of functions to support the development of machine learning algorithms.

Framework that implements AutoML algorithms for model architecture search at scale.

Parris, the automated infrastructure setup tool for machine learning algorithms.