618 Repositories
Python regression-algorithms Libraries
Image Encryption/Decryption based on Rubik Cube 's principle and AES
Image Encryption/Decryption based on Rubik Cube 's principle and AES Our final project for Theory of Crytography class. Our Image Encryption/Decryptio
RL Algorithms with examples in Python / Pytorch / Unity ML agents
Reinforcement Learning Project This project was created to make it easier to get started with Reinforcement Learning. It now contains: An implementati
Sentiment-Analysis and EDA on the IMDB Movie Review Dataset
Sentiment-Analysis and EDA on the IMDB Movie Review Dataset The main part of the work focuses on the exploration and study of different approaches whi
To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types
To Design and Implement Logistic Regression to Classify Between Benign and Malignant Cancer Types, from a Database Taken From Dr. Wolberg reports his Clinic Cases.
Python Machine Learning Jupyter Notebooks (ML website)
Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also
Logistic Bandit experiments. Official code for the paper "Jointly Efficient and Optimal Algorithms for Logistic Bandits".
Code for the paper Jointly Efficient and Optimal Algorithms for Logistic Bandits, by Louis Faury, Marc Abeille, Clément Calauzènes and Kwang-Sun Jun.
This package implements the algorithms introduced in Smucler, Sapienza, and Rotnitzky (2020) to compute optimal adjustment sets in causal graphical models.
optimaladj: A library for computing optimal adjustment sets in causal graphical models This package implements the algorithms introduced in Smucler, S
Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models
tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener
An NUS timetable generator which uses a genetic algorithm to optimise timetables to suit the needs of NUS students.
A timetable optimiser for NUS which uses an evolutionary algorithm to "breed" a timetable suited to your needs.
Machine Learning Course with Python:
A Machine Learning Course with Python Table of Contents Download Free Deep Learning Resource Guide Slack Group Introduction Motivation Machine Learnin
This repo contains the implementation of YOLOv2 in Keras with Tensorflow backend.
Easy training on custom dataset. Various backends (MobileNet and SqueezeNet) supported. A YOLO demo to detect raccoon run entirely in brower is accessible at https://git.io/vF7vI (not on Windows).
🙄 Difficult algorithm, Simple code.
🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin
The Qis|krypt⟩ is a software suite of protocols of quantum cryptography and quantum communications
The Qis|krypt⟩ is a software suite of protocols of quantum cryptography and quantum communications, as well, other protocols and algorithms, built using IBM’s open-source Software Development Kit for quantum computing Qiskit. ⚛️ 🔐
A High-Quality Real Time Upscaler for Anime Video
Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua
Pure python implementations of popular ML algorithms.
Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks
A collection of data structures and algorithms I'm writing while learning
Data Structures and Algorithms: This is a collection of data structures and algorithms that I write while learning the subject Stack: stack.py A stack
A simple flask application to collect annotations for the Turing Change Point Dataset, a benchmark dataset for change point detection algorithms
AnnotateChange Welcome to the repository of the "AnnotateChange" application. This application was created to collect annotations of time series data
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals
Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection
Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d
Survival analysis in Python
What is survival analysis and why should I learn it? Survival analysis was originally developed and applied heavily by the actuarial and medical commu
The Turing Change Point Detection Benchmark: An Extensive Benchmark Evaluation of Change Point Detection Algorithms on real-world data
Turing Change Point Detection Benchmark Welcome to the repository for the Turing Change Point Detection Benchmark, a benchmark evaluation of change po
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
Where-Got-Time - An NUS timetable generator which uses a genetic algorithm to optimise timetables to suit the needs of NUS students
Where Got Time(table)? A timetable optimsier which uses an evolutionary algorith
PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/temporal/spatiotemporal databases
Introduction PAMI stands for PAttern MIning. It constitutes several pattern mining algorithms to discover interesting patterns in transactional/tempor
General Assembly's 2015 Data Science course in Washington, DC
DAT8 Course Repository Course materials for General Assembly's Data Science course in Washington, DC (8/18/15 - 10/29/15). Instructor: Kevin Markham (
A middle-to-high level algorithm book designed with coding interview at heart!
Hands-on Algorithmic Problem Solving A one-stop coding interview prep book! About this book In short, this is a middle-to-high level algorithm book de
Add any Program in any language you like or add a hello world Program ❣️ if you like give us :star:
Welcome to the Hacktoberfest 2018 Hello-world 📋 This Project aims to help you to get started with using Github. You can find a tutorial here What is
A toolkit for controlling Euro Truck Simulator 2 with python to develop self-driving algorithms.
europilot Overview Europilot is an open source project that leverages the popular Euro Truck Simulator(ETS2) to develop self-driving algorithms. A con
Python bindings for Basler's VisualApplets TCL script generation
About visualapplets.py The Basler AG company provides a TCL scripting engine to automatize the creation of VisualApplets designs (a former Silicon Sof
Python Client for Algorithmia Algorithms and Data API
Algorithmia Common Library (python) Python client library for accessing the Algorithmia API For API documentation, see the PythonDocs Algorithm Develo
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame
Algorithms written in different programming languages
Data Structures and Algorithms Clean example implementations of data structures and algorithms written in different languages. List of implementations
A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented in Python.
Reinforcement-Learning-Notebooks A collection of Reinforcement Learning algorithms from Sutton and Barto's book and other research papers implemented
An AI made using artificial intelligence (AI) and machine learning algorithms (ML) .
DTech.AIML An AI made using artificial intelligence (AI) and machine learning algorithms (ML) . This is created by help of some members in my team and
Reinforcement learning algorithms in RLlib
raylab Reinforcement learning algorithms in RLlib and PyTorch. Installation pip install raylab Quickstart Raylab provides agents and environments to b
A collection of implementations of deep domain adaptation algorithms
Deep Transfer Learning on PyTorch This is a PyTorch library for deep transfer learning. We divide the code into two aspects: Single-source Unsupervise
Masked regression code - Masked Regression
Masked Regression MR - Python Implementation This repositery provides a python implementation of MR (Masked Regression). MR can efficiently synthesize
Iowa Project - My second project done at General Assembly, focused on feature engineering and understanding Linear Regression as a concept
Project 2 - Ames Housing Data and Kaggle Challenge PROBLEM STATEMENT Inferring or Predicting? What's more valuable for a housing model? When creating
A video scene detection algorithm is designed to detect a variety of different scenes within a video
Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.
Benchmark spaces - Benchmarks of how well different two dimensional spaces work for clustering algorithms
benchmark_spaces Benchmarks of how well different two dimensional spaces work fo
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work
BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it
Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.
Awesome-AI-books - Some awesome AI related books and pdfs for learning and downloading
Awesome AI books Some awesome AI related books and pdfs for downloading and learning. Preface This repo only used for learning, do not use in business
Most popular metrics used to evaluate object detection algorithms.
Most popular metrics used to evaluate object detection algorithms.
PySOT - SenseTime Research platform for single object tracking, implementing algorithms like SiamRPN and SiamMask.
PySOT is a software system designed by SenseTime Video Intelligence Research team. It implements state-of-the-art single object tracking algorit
Gans-in-action - Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models
Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor
Numerical-computing-is-fun - Learning numerical computing with notebooks for all ages.
As much as this series is to educate aspiring computer programmers and data scientists of all ages and all backgrounds, it is also a reminder to mysel
PathPlanning - Common used path planning algorithms with animations.
Overview This repository implements some common path planning algorithms used in robotics, including Search-based algorithms and Sampling-based algori
LinearRegression2 Tvads and CarSales
LinearRegression2_Tvads_and_CarSales This project infers the insight that how the TV ads for cars and car Sales are being linked with each other. It i
Distributed-systems-algos - Distributed Systems Algorithms For Python
Distributed Systems Algorithms ISIS algorithm In an asynchronous system that kee
Price-Prediction-For-a-Dream-Home - A machine learning based linear regression trained model for house price prediction.
Price-Prediction-For-a-Dream-Home ROADMAP TO THIS LINEAR REGRESSION BASED HOUSE PRICE PREDICTION PREDICTION MODEL Import all the dependencies of the p
Image-popularity-score - A novel deep regression method for image scoring.
Image-popularity-score - A novel deep regression method for image scoring.
Constrained Logistic Regression - How to apply specific constraints to logistic regression's coefficients
Constrained Logistic Regression Sample implementation of constructing a logistic regression with given ranges on each of the feature's coefficients (v
Optimizers-visualized - Visualization of different optimizers on local minimas and saddle points.
Optimizers Visualized Visualization of how different optimizers handle mathematical functions for optimization. Contents Installation Usage Functions
Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan
Solar-radiation-ISB-MLOps - Flask app to predict daily radiation from the time series of Solcast from Islamabad, Pakistan.
A minimal implementation of Gaussian process regression in PyTorch
pytorch-minimal-gaussian-process In search of truth, simplicity is needed. There exist heavy-weighted libraries, but as you know, we need to go bare b
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Semi-supervised Deep Kernel Learning This is the code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data
Python implementation of Aho-Corasick algorithm for string searching
Python implementation of Aho-Corasick algorithm for string searching
A curated list of awesome Model-Based RL resources
Awesome Model-Based Reinforcement Learning This is a collection of research papers for model-based reinforcement learning (mbrl). And the repository w
A Python Package for Convex Regression and Frontier Estimation
pyStoNED pyStoNED is a Python package that provides functions for estimating multivariate convex regression, convex quantile regression, convex expect
Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible
Python script that analyses the given datasets and comes up with the best polynomial regression representation with the smallest polynomial degree possible, to be the most reliable with the least complexity possible
NOMAD - A blackbox optimization software
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Using Bayesian, KNN, Logistic Regression to classify spam and non-spam.
Make Sure the dataset file "spamData.mat" is in the folder spam\src Environment: Python --version = 3.7 Third Party: numpy, matplotlib, math, scipy
Data Model built using Logistic Regression Algorithm on Python.
Logistic-Regression Problem Statement: Your client is a retail banking institution. Term deposits are a major source of income for a bank. A term depo
Using python 3 and Flask an MVC system where the AES 128 CBC and Trivium algorithms
This project was developed using python 3 and Flask, it is an MVC system where the AES 128 CBC and Trivium algorithms can be tested through a communication between the computer and a device such as a microcontroller that provides these algorithms.
LynxKite: a complete graph data science platform for very large graphs and other datasets.
LynxKite is a complete graph data science platform for very large graphs and other datasets. It seamlessly combines the benefits of a friendly graphical interface and a powerful Python API.
Implemented four supervised learning Machine Learning algorithms
Implemented four supervised learning Machine Learning algorithms from an algorithmic family called Classification and Regression Trees (CARTs), details see README_Report.
A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation.
Continuous Wasserstein-2 Benchmark This is the official Python implementation of the NeurIPS 2021 paper Do Neural Optimal Transport Solvers Work? A Co
Decision Tree Regression algorithm implemented on Python from scratch.
Decision_Tree_Regression I implemented the decision tree regression algorithm on Python. Unlike regular linear regression, this algorithm is used when
SciPy library main repository
SciPy SciPy (pronounced "Sigh Pie") is an open-source software for mathematics, science, and engineering. It includes modules for statistics, optimiza
Touca SDK for Python
Touca SDK For Python Touca helps you understand the true impact of your day to day code changes on the behavior and performance of your overall softwa
Machine learning algorithms for many-body quantum systems
NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and
No-reference Image Quality Assessment(NIQA) Algorithms (BRISQUE, NIQE, PIQE, RankIQA, MetaIQA)
No-Reference Image Quality Assessment Algorithms No-reference Image Quality Assessment(NIQA) is a task of evaluating an image without a reference imag
A Comparative Review of Recent Kinect-Based Action Recognition Algorithms (TIP2020, Matlab codes)
A Comparative Review of Recent Kinect-Based Action Recognition Algorithms This repo contains: the HDG implementation (Matlab codes) for 'Analysis and
Repository for Comparison based sorting algorithms in python
Repository for Comparison based sorting algorithms in python. This was implemented for project one submission for ITCS 6114 Data Structures and Algorithms under the guidance of Dr. Dewan at the University of North Carolina at Charlotte, Fall 2021.
LTGen provides classic algorithms used in Language Theory.
LTGen LTGen stands for Language Theory GENerator and provides tools to implement language theory. Command Line LTGen is a collection of tools to imple
A parallel branch-and-bound engine for Python.
pybnb A parallel branch-and-bound engine for Python. This software is copyright (c) by Gabriel A. Hackebeil (gabe.hacke
scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms.
Sklearn-genetic-opt scikit-learn models hyperparameters tuning and feature selection, using evolutionary algorithms. This is meant to be an alternativ
Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
Codes-for-Algorithms Codes for realizing theories learned from Data Mining, Machine Learning, Deep Learning without using the present Python packages.
DANet for Tabular data classification/ regression.
Deep Abstract Networks A pyTorch implementation for AAAI-2022 paper DANets: Deep Abstract Networks for Tabular Data Classification and Regression. Bri
A hackerank problems, solution repository
This is a repository for all hackerank challenges kindly note this is for learning purposes and if you wish to contribute, dont hesitate all submision
CacheControl is a port of the caching algorithms in httplib2 for use with requests session object.
CacheControl CacheControl is a port of the caching algorithms in httplib2 for use with requests session object. It was written because httplib2's bett
A web application using [FastAPI + streamlit + Docker] Neural Style Transfer (NST) refers to a class of software algorithms that manipulate digital images
Neural Style Transfer Web App - [FastAPI + streamlit + Docker] NST - application based on the Perceptual Losses for Real-Time Style Transfer and Super
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs
Hierarchical Clustering: O(1)-Approximation for Well-Clustered Graphs This repository contains code to accompany the paper "Hierarchical Clustering: O
Webtesting for course Data Structures & Algorithms
Selenium job to automate queries to check last posts of Module Data Structures & Algorithms Web-testing for course Data Structures & Algorithms Struct
MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine Learning work with thousands of other users.
The collaboration platform for Machine Learning MLReef is an open source ML-Ops platform that helps you collaborate, reproduce and share your Machine
PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
PyGAD: Genetic Algorithm in Python PyGAD is an open-source easy-to-use Python 3 library for building the genetic algorithm and optimizing machine lear
Learning with Subset Stacking
Learning with Subset Stacking (LESS) LESS is a new supervised learning algorithm that is based on training many local estimators on subsets of a given
Mercer Gaussian Process (MGP) and Fourier Gaussian Process (FGP) Regression
Mercer Gaussian Process (MGP) and Fourier Gaussian Process (FGP) Regression We provide the code used in our paper "How Good are Low-Rank Approximation
codes for Self-paced Deep Regression Forests with Consideration on Ranking Fairness
Self-paced Deep Regression Forests with Consideration on Ranking Fairness This is official codes for paper Self-paced Deep Regression Forests with Con
AlgoVision - A Framework for Differentiable Algorithms and Algorithmic Supervision
NeurIPS 2021 Paper "Learning with Algorithmic Supervision via Continuous Relaxations"
Diverse graph algorithms implemented using JGraphT library.
# 1. Installing Maven & Pandas First, please install Java (JDK11) and Python 3 if they are not already. Next, make sure that Maven (for importing J
Code for the paper "Learning-Augmented Algorithms for Online Steiner Tree"
Learning-Augmented Algorithms for Online Steiner Tree This is the code for the paper "Learning-Augmented Algorithms for Online Steiner Tree". Requirem
Ml based project which uses regression technique to predict the price.
Price-Predictor Ml based project which uses regression technique to predict the price. I have used various regression models and finds the model with
Distributed algorithms, reimplemented for fun and practice
Distributed Algorithms Playground for reimplementing and experimenting with algorithms for distributed computing. Usage Running the code for Ring-AllR
Algorithms and utilities for SAR sensors
WARNING: THIS CODE IS NOT READY FOR USE Sarsen Algorithms and utilities for SAR sensors Objectives Be faster and simpler than ESA SNAP and cloud nativ