Copyright (C) 2016-2018 AutoML Group Attention: This package is a reimplementation of the original SMAC tool (see reference below). However, the reimplementation slightly differs from the original SMAC. For comparisons against the original SMAC, we refer to a stable release of SMAC (v2) in Java which can be found here. The documentation can be found here. Status for master branch: Status for the development branch SMAC is a tool for algorithm configuration to optimize the parameters of arbitrary algorithms across […]

Khiva Khiva is an open-source library of efficient algorithms to analyse time series in GPU and CPU. It can be used to extract insights from one or a group of time series. The large number of available methods allow us to understand the nature of each time series. Based on the results of this analysis, users can reduce dimensionality, find out recurrent motifs or discords, understand the seasonality or trend from a given time series, forecasting and detect anomalies. Khiva […]

Paper-Reviewer Matcher A python package for paper-reviewer matching algorithm based on topic modeling and linear programming. The algorithm is implemented based on this article). This package solves problem of assigning paper to reviewers with constrains by solving linear programming problem. We minimize global distance between papers and reviewers in topic space (e.g. topic modeling can be Principal component, Latent Semantic Analysis (LSA), etc.). Here is a diagram of problem setup and how we solve the problem. Mind-Match Command Line Mind-Match […]

Algorithmic-Maze-Runner A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic) Running the .py File Clone the repository Install dependencies by entering pip install – r requirements.txt Run the .py file Files main.py: python file for application main.exe: executable version of main.py GitHub https://github.com/flintlok/Algorithmic-Maze-Runner    

PPO Pytorch C++ This is an implementation of the proximal policy optimization algorithm for the C++ API of Pytorch. It uses a simple TestEnvironment to test the algorithm. Below is a small visualization of the environment, the algorithm is tested in. Build You first need to install PyTorch. For a clean installation from Anaconda, checkout this short tutorial, or this tutorial, to only install the binaries. Do mkdir build cd build cmake -DCMAKE_PREFIX_PATH=/absolut/path/to/libtorch .. make Run Run the executable with […]

ska Lets you easily sign data, using symmetric-key algorithm encryption. Allows you to validate signed data and identify possible validation errors. Uses sha-(1, 224, 256, 385 and 512)/hmac for signature encryption. Allows to use custom hash algorithms. Comes with shortcut functions for signing (and validating) dictionaries and URLs. Key concepts Hosts, that communicate with each other, share the Secret Key, which is used to sign data (requests). Secret key is never sent around. One of the cases is signing of […]

pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and motion planning (TAMP). This repository was originally developed for the PDDLStream (previously named STRIPStream) approach to TAMP. With the help of Yijiang Huang, a stable and documented fork of pybullet-planning named pybullet_planning is available through PyPI. However, new features will continue to be introduced first through pybullet-planning. Installation Install for macOS or Linux using: pybullet-planning is intended to have ongoing support for […]

Cutting Stock Problem Cutting Stock Problem (CSP) deals with planning the cutting of items (rods / sheets) from given stock items (which are usually of fixed size). Quick Usage This is how CSP Tools looks in action. Click CSP Tool to use it Libraries Quick Start Install Pipenv, if not already installed $ pip3 install –user pipenv Clone this project and install packages $ git clone https://github.com/emadehsan/csp $ cd csp $ pipenv install # activate env $ pipenv shell Run […]

8QueensGenetic A Python project for optimizing the 8 Queens Puzzle using the Genetic Algorithm implemented in PyGAD. The project uses the Kivy cross-platform Python framework for building the GUI of the 8 queens puzzle. The GUI helps to visualize the solutions reached while the genetic algorithm (GA) is optimizing the problem to find the best solution. For implementing the genetic algorithm, the PyGAD library is used. Check its documentation here: https://pygad.readthedocs.io To install PyGAD, simply use pip to download and […]

Artificial Neural Network This repository contain implementation of Artificial Neural Network Algorithm in several programming languanges and frameworks. This repository was created to introduce artifical neural network in a simple way. Artificial Neural Network has become popular at this time. This branch field of Artificial Intelligence has given powerful impact to our daily life such as social media recomendation system, face detection of camera on phone and many more. Therefore, to keep up our knowledge in technology especially Artificial Intelligence, […]