scikit-multimodallearn scikit-multimodallearn is a Python package implementing algorithms multimodal data. It is compatible with scikit-learn, a popularpackage for machine learning in Python. Documentation The documentation including installation instructions, API documentationand examples isavailable online. Installation Dependencies scikit-multimodallearn works with Python 3.5 or later. scikit-multimodallearn depends on scikit-learn (version >= 0.19). Optionally, matplotlib is required to run the examples. Installation using pip scikit-multimodallearn isavailable on PyPIand can be installed using pip: pip install scikit-multimodallearn Development The development of this package follows the […]

Snowball is a small string processing language for creating stemming algorithms for use in Information Retrieval, plus a collection of stemming algorithms implemented using it. Snowball was originally designed and built by Martin Porter. Martin retired from development in 2014 and Snowball is now maintained as a community project. Martin originally chose the name Snowball as a tribute to SNOBOL, the excellent string handling language from the 1960s. It now also serves as a metaphor for how the project grows […]

RayLink is a RL framework used to build and train RL algorithms. RayLink was used to build a RL framework, andtested in a large-scale multi-agent training environment. It can help you easily build your own workload.RayLink will connect every working node, and let you efficiently arrange your own dataflow. Because you can define anode type based on its functionality, all dataflow are more clear to researchers and developers. It’s based on ray for now, and it has implemented several new […]

This repository is a compilation of important Data Structures and Algorithms based on Python. Please make seperate folders for different topics😇 The following topics will be elaborated: Big O Time Complexity Tuples Dictionaries Lists Arrays Looping Sorting Algorithms Bubble Sort Selection Sort Insertion Sort Bucket Sort Merge Sort Quick Sort Heap Sort Tree Sort Shell Sort Count Sort Radix Sort Searching Algorithms Linear Search Binary Search Backtracking Dynamic Programming Linked List Singly Linked List Doubly Linked List Circular Singly Linked […]

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 […]