Python Regression-algorithms Resources

RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for

Balanced MSE Code for the paper: Balanced MSE for Imbalanced Visual Regression Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Ziwei Liu CVPR 2022 (Oral) News

DEEP LEARNING FOR CODERS WITH FASTAI AND PYTORCH The repository contains a list of the projects which I have worked on while reading the book Deep Lea

AutoTrader AutoTrader is Python-based platform intended to help in the development, optimisation and deployment of automated trading systems. From sim

Best Data Science Resources Hey, Data Enthusiasts out there! Finally, after lots of requests from the community I finally came up with the best free D

ML-ProjectKart 📌 Repository This kart showcases the finest collection of all projects based on machine learning, deep learning, computer vision, natu

👏 Pre- requisites to Machine Learning

Multi-Type-TD-TSR Check it out on Source Code of our Paper: Multi-Type-TD-TSR Extracting Tables from Document Images using a Multi-stage Pipeline for

DodgeDrone: Vision-based Agile Drone Flight (ICRA 2022 Competition) Would you like to push the boundaries of drone navigation? Then participate in the

Ana's Portfolio ✌️ Welcome to my Portfolio! You will find here different Projects I have worked on (from scratch) 💪 Projects 💻 1️⃣ Hangman game (Mad

💎A high level pipeline for face landmarks detection, supports training, evaluating, exporting, inference and 100+ data augmentations, compatible with torchvision and albumentations, can easily install with pip.

WIE-WoC IEEE-WIE presents WIE Week of Code (WIEWoC), a 3-days long open-source contribution event starting from 1st March, highlighting different pyth

AI Seed Projects Start with ready code for your next AI experiment. Choose from 1000+ code templates, across a wide variety of use cases. All examples

Machine Learning With Python Get started with Machine Learning with Python An engaging introduction to Machine Learning with Python TL;DR Download all

Billion-Scale ANN http://big-ann-benchmarks.com/ Install The only prerequisite is Python (tested with 3.6) and Docker. Works with newer versions of Py

Basic Machine Learning Algorithms All the basic Machine Learning Algorithms are implemented in Python using libraries Acknowledgements Machine Learnin

Eigenlearning This repo contains code for replicating the experiments of the paper A Theory of the Inductive Bias and Generalization of Kernel Regress

Soomvaar 📌 Introduction Soomvaar is the collection of various codes implement in machine learning and machine learning algorithms with python on coll

HandLer This repository contains the code and data for the following paper: Forward Propagation, Backward Regression, and Pose Association for Hand Tr

SCALoss PyTorch implementation of the paper "SCALoss: Side and Corner Aligned Loss for Bounding Box Regression" (AAAI 2022). Introduction IoU-based lo

hyperbox-brain is a Python open source toolbox implementing hyperbox-based machine learning algorithms built on top of scikit-learn and is distributed

Overview of Credit Card Analysis In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm

Data Structures and Algorithms All the essential resources and template code nee

Regression Free Model Update Code for the paper: Regression Bugs Are In Your Mod

How does the encrypter works? Transform your text into encrypted symbols using t

event-forecasting Event Forecasting Algorithms Theory Correlating events in comp

Graph Data Science: an abstraction layer in Python for building knowledge graphs, integrated with popular graph libraries – atop Pandas, RDFlib, pySHACL, RAPIDS, NetworkX, iGraph, PyVis, pslpython, pyarrow, etc.

Vaex-Big-Data-Analytics-for-Airline-data A Python notebook (ipynb) created in Jupyter Notebook, which utilizes the Vaex library for Big Data Analytics

Cormen Lib Sample Problems Description This repository contnains sample problems with test cases using Cormen-Lib. These problems were made for the pu

Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.

evolvingrl Supplementary Data for Evolving Reinforcement Learning Algorithms This dataset contains 1000 loss graphs from two experiments: 500 unique g

NATS-Bench: Benchmarking NAS Algorithms for Architecture Topology and Size Xuanyi Dong, Lu Liu, Katarzyna Musial, Bogdan Gabrys in IEEE Transactions o

QDax: Accelerated Quality-Diversity QDax is a tool to accelerate Quality-Diveristy (QD) algorithms through hardware accelerators and massive paralleli

GeneDisco is a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.

LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer

Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features

Python red-black trees A Python implementation of red-black trees. This code was originally copied from programiz.com, but I have made a few tweaks to

Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu

Nonlinear Optimization Algorithms During my time as Scientific Assistant at the Karlsruhe Institute of Technology (Germany) I implemented various Opti

CLASSIX Fast and explainable clustering based on sorting CLASSIX is a fast and explainable clustering algorithm based on sorting. Here are a few highl

Brainda Welcome! First and foremost, Welcome! Thank you for visiting the Brainda repository which was initially released at this repo and reorganized

Codenames Code infrastructure and player algorithms for the Codenames board game. This is the active fork of mkali-personal/codenames. Intro This is b

Implementations of the algorithms in the paper Approximative Algorithms for Multi-Marginal Optimal Transport and Free-Support Wasserstein Barycenters

Fliscopt FLIght SCheduling OPTimization 🛫 or fliscopt is a simple optimization library for flight scheduling and related problems in the discrete dom

Current gate-based quantum computers have the potential to provide a computational advantage if algorithms use quantum hardware efficiently.

Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se

Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them.

Multiple-Linear-Regression-master - A python program to implement Multiple Linear Regression using the LinearRegression class from sklearn.linear model library

Balabobapy - Using artificial intelligence algorithms to continue the text

Intro-to-Data-Science Conducted ANOVA and Logistic regression analysis. Project ANOVA The main aim of this project is to perform One-Way ANOVA analysi

Demo-of-MCMC These files are based on the class materials of AEROSP 567 taught by Prof. Alex Gorodetsky at University of Michigan. Author: Hung-Hsiang

This machine learning model was developed for House Prices - Advanced Regression Techniques competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed model for heart failure prediction accuracy of 88 percent.

Basic sort and search algorithms written in python. These were all developed as part of my Computer Science course to demonstrate understanding so they aren't 100% efficent

Genetic algorithms are heuristic search algorithms inspired by the process that supports the evolution of life. The algorithm is designed to replicate the natural selection process to carry generation, i.e. survival of the fittest of beings.

Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme

CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c

Logistic Regression Advanced Case Study Gender Classification: Predicting a person's gender based on their weight and height 1. Introduction We turn o

Breast-Cancer-Classification - Using SKLearn breast cancer dataset which contains 569 examples and 32 features classifying has been made with 6 different algorithms

Using Logistic Regression and classifiers of the dataset to produce an accurate recall, f-1 and precision score

Acceder al código desde Google Colab para poder ver de manera adecuada todas las visualizaciones y poder interactuar con ellas. Links de acceso: Noteb

Self-supervised learning Self-supervised learning algorithms provide a way to train Deep Neural Networks in an unsupervised way using contrastive loss

An implementation of the Fibonacci method for gradient descent, featuring a TKinter GUI for inputting the function / parameters to be examined and a matplotlib plot of the function and results.

User-centered Regression An Approach to Explore Logistic Regression Models This tool applies the potential of Attribute-RadViz in identifying correlat

Pearl The Parallel Evolutionary and Reinforcement Learning Library (Pearl) is a pytorch based package with the goal of being excellent for rapid proto

The purpose of this project is create a classification model capable of accurately predicting the price of secondhand cars. The data used for model building is open source and has been added to this repository. Most packages used are usually pre-installed in most developed environments and tools like collab, jupyter, etc. This can be useful for people looking to enhance the way the code their predicitve models and efficient ways to deal with tabular data!

The purpose of this project is create a predictive model capable of identifying the probability of a person securing an admit based on their personal profile parameters. Simplified visualisations have been created for understanding the data. 80% accuracy was achieved on the test set.

eo-grow Earth observation framework for scaled-up processing in Python. Analyzing Earth Observation (EO) data is complex and solutions often require c

Final Project for Practical Python Programming and Algorithms for Data Analysis (PHW2781L, Summer 2020) Redlining, Race-Exclusive Deed Restriction Lan

Wordle Game This is a python implementation of wordle, which uses the same set of available words as the hit game, Wordle. Play the game manually pyth

Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of

scikit-event-correlation Event Correlation and Changing Detection Algorithm Theo

Hitters_Linear_Regression Kullanacağımız veri seti Carnegie Mellon Üniversitesi'

A library for benchmarking, developing and deploying deep learning anomaly detection algorithms Key Features • Getting Started • Docs • License Introd

Tools for mathematical optimization region

The Cormen-lib module is an insular data structures and algorithms library based on the Thomas H. Cormen's Introduction to Algorithms Third Edition. This library was made specifically for administering and grading assignments related to data structure and algorithms in computer science.

package tests docs license stats support This repository contains FEDOT - an open-source framework for automated modeling and machine learning (AutoML

ParaMonte is a serial/parallel library of Monte Carlo routines for sampling mathematical objective functions of arbitrary-dimensions, in particular, the posterior distributions of Bayesian models in data science, Machine Learning, and scientific inference, with the design goal of unifying the automation (of Monte Carlo simulations), user-friendliness (of the library), accessibility (from multiple programming environments), high-performance (at runtime), and scalability (across many parallel processors).

BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor

**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S

Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.

implementation of machine learning Algorithms such as decision tree and random forest and xgboost on darasets then compare results for each and implement ant colony and genetic algorithms on tsp map, play blackjack game and robot in grid world and evaluate reward for it

100 Days of Code Learning program to keep a habit of coding daily and learn things at your own pace with help from our remote community.

Algo_Visualizer This project is an Algorithm Visualizer where a user can visualize common algorithms like "Bubble Sort", "Merge Sort", "Quick Sort", "

Call of Duty World League: Search & Destroy Outcome Predictions Growing up as an avid Call of Duty player, I was always curious about what factors led

ML_Model_implementaion Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other dectree_model: Implementation o

DataScience_ML_and_Python Repo contains Python Code Reference to learn Python in a week, It also contains Machine Learning Algorithms and some example

EncypherUtil Simple encryption/decryption utility using PyCryptodome module. Working with AES and RSA algorithms. THIS UTILITY IS NOT LICENSED AS CRYP

A malware to encrypt all the .txt and .jpg files in target computer using RSA algorithms. Change the Blackgound image of targets' computer. and decrypt the targets' encrypted files in our own computer

Algorithms-in-Python Programs related to DSA in Python for placement practice CO

Policy Gradient Algorithms From Scratch (NumPy) This repository showcases two policy gradient algorithms (One Step Actor Critic and Proximal Policy Op

Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python

Meta learning algorithms to train cross-lingual NLI (multi-task) models

SimReg: A Simple Regression Based Framework for Self-supervised Knowledge Distillation Source code for the paper "SimReg: Regression as a Simple Yet E

Sorting-Algorithms - All information about sorting algorithm you need and you can visualize the code tracer

Diabetes Prediction Using SVM I explore a diabetes prediction algorithm using a Diabetes dataset. Using a Support Vector Machine for my prediction alg

Matchmaker Algorithmic Multi-Instrumental MIDI Continuation Implementation Taming large-scale MIDI datasets with algorithms This is a WIP so please ch

Arithmos Cipher is a simple Cryptography that I created myself in Python

Algorithms Classic algorithms including Fizz Buzz, Bubble Sort, the Fibonacci Sequence, a Sudoku solver, and more. Algorithm Complexity Time and Space

SortingAlgorithmVisualization A place for me to learn about sorting algorithms.