274 Repositories
Python Faster-Convex-Lipschitz-Regression Libraries
Repository for RNNs using TensorFlow and Keras - LSTM and GRU Implementation from Scratch - Simple Classification and Regression Problem using RNNs
RNN 01- RNN_Classification Simple RNN training for classification task of 3 signal: Sine, Square, Triangle. 02- RNN_Regression Simple RNN training for
Open-Source CI/CD platform for ML teams. Deliver ML products, better & faster. ⚡️🧑🔧
Deliver ML products, better & faster Giskard is an Open-Source CI/CD platform for ML teams. Inspect ML models visually from your Python notebook 📗 Re
[CVPR 2022 Oral] Balanced MSE for Imbalanced Visual Regression https://arxiv.org/abs/2203.16427
Balanced MSE Code for the paper: Balanced MSE for Imbalanced Visual Regression Jiawei Ren, Mingyuan Zhang, Cunjun Yu, Ziwei Liu CVPR 2022 (Oral) News
I will implement Fastai in each projects present in this repository.
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
This repository contains implementations of all Machine Learning Algorithms from scratch in Python. Mathematics required for ML and many projects have also been included.
👏 Pre- requisites to Machine Learning
torchlm is aims to build a high level pipeline for face landmarks detection, it supports training, evaluating, exporting, inference(Python/C++) and 100+ data augmentations
💎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.
Get started with Machine Learning with Python - An introduction with Python programming examples
Machine Learning With Python Get started with Machine Learning with Python An engaging introduction to Machine Learning with Python TL;DR Download all
codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"
Eigenlearning This repo contains code for replicating the experiments of the paper A Theory of the Inductive Bias and Generalization of Kernel Regress
Forward Propagation, Backward Regression and Pose Association for Hand Tracking in the Wild (CVPR 2022)
HandLer This repository contains the code and data for the following paper: Forward Propagation, Backward Regression, and Pose Association for Hand Tr
SCALoss: Side and Corner Aligned Loss for Bounding Box Regression (AAAI2022).
SCALoss PyTorch implementation of the paper "SCALoss: Side and Corner Aligned Loss for Bounding Box Regression" (AAAI 2022). Introduction IoU-based lo
NoSecerets is a python script that is designed to crack hashes extremely fast. Faster even than Hashcat
NoSecerets NoSecerets is a python script that is designed to crack hashes extremely fast. Faster even than Hashcat How does it work? Instead of taking
Transformers-regression - Regression Bugs Are In Your Model! Measuring, Reducing and Analyzing Regressions In NLP Model Updates
Regression Free Model Update Code for the paper: Regression Bugs Are In Your Mod
Vaex library for Big Data Analytics of an Airline dataset
Vaex-Big-Data-Analytics-for-Airline-data A Python notebook (ipynb) created in Jupyter Notebook, which utilizes the Vaex library for Big Data Analytics
Image-to-image regression with uncertainty quantification in PyTorch
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.
To build a regression model to predict the concrete compressive strength based on the different features in the training data.
Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features
Artificial Neural network regression model to predict the energy output in a combined cycle power plant.
Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu
Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression
Regression Transformer Codebase to experiment with a hybrid Transformer that combines conditional sequence generation with regression . Development se
Stopmagic gives you the power of creating amazing Stop Motion animations faster and easier than ever before.
Stopmagic gives you the power of creating amazing Stop Motion animations faster and easier than ever before. This project is maintained by Aldrin Mathew.
Multiple Linear Regression using the LinearRegression class from sklearn.linear_model library
Multiple-Linear-Regression-master - A python program to implement Multiple Linear Regression using the LinearRegression class from sklearn.linear model library
Conducted ANOVA and Logistic regression analysis using matplot library to visualize the result.
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
This machine learning model was developed for House Prices
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)
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.
Predicting a person's gender based on their weight and height
Logistic Regression Advanced Case Study Gender Classification: Predicting a person's gender based on their weight and height 1. Introduction We turn o
Lipschitz-constrained Unsupervised Skill Discovery
Lipschitz-constrained Unsupervised Skill Discovery This repository is the official implementation of Seohong Park, Jongwook Choi*, Jaekyeom Kim*, Hong
Using Logistic Regression and classifiers of the dataset to produce an accurate recall, f-1 and precision score
Using Logistic Regression and classifiers of the dataset to produce an accurate recall, f-1 and precision score
An Approach to Explore Logistic Regression Models
User-centered Regression An Approach to Explore Logistic Regression Models This tool applies the potential of Attribute-RadViz in identifying correlat
Title: Graduate-Admissions-Predictor
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.
The Dual Memory is build from a simple CNN for the deep memory and Linear Regression fro the fast Memory
Simple-DMA a simple Dual Memory Architecture for classifications. based on the paper Dual-Memory Deep Learning Architectures for Lifelong Learning of
Hitters Linear Regression - Hitters Linear Regression With Python
Hitters_Linear_Regression Kullanacağımız veri seti Carnegie Mellon Üniversitesi'
A faster copy of nell's comet nuker
Astro a faster copy of nell's comet nuker also nell uses external libraries like it's cocaine man never learned to use ansi color codes (ily nell) (On
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
ESGD-M - A stochastic non-convex second order optimizer, suitable for training deep learning models, for PyTorch
Used Logistic Regression, Random Forest, and XGBoost to predict the outcome of Search & Destroy games from the Call of Duty World League for the 2018 and 2019 seasons.
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
Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other
ML_Model_implementaion Implementation of ML models like Decision tree, Naive Bayes, Logistic Regression and many other dectree_model: Implementation o
Node-level Graph Regression with Deep Gaussian Process Models
Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python
Source code for the BMVC-2021 paper "SimReg: Regression as a Simple Yet Effective Tool for Self-supervised Knowledge Distillation".
SimReg: A Simple Regression Based Framework for Self-supervised Knowledge Distillation Source code for the paper "SimReg: Regression as a Simple Yet E
This repo is duplication of jwyang/faster-rcnn.pytorch
Faster RCNN Pytorch This repo is duplication of jwyang/faster-rcnn.pytorch C/C++ code are removed and easier to study. Python 3.8.5 Ubuntu 20.04.1 LTS
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
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
[Pedestron] Generalizable Pedestrian Detection: The Elephant In The Room. @ CVPR2021
Pedestron Pedestron is a MMdetection based repository, that focuses on the advancement of research on pedestrian detection. We provide a list of detec
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
Make YouTube videos tasks in Todoist faster and time efficient!
Youtubist Basically fork of yt-dlp python module to my needs. You can paste playlist or channel link on the YouTube. It will automatically format to s
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
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
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 (
Bottom-up attention model for image captioning and VQA, based on Faster R-CNN and Visual Genome
bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at
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
Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning
CSRL Implementation of CSRL from the AAAI2022 paper: Constraint Sampling Reinforcement Learning: Incorporating Expertise For Faster Learning Python: 3
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
Contrastive Unpaired Translation (CUT) video (1m) | video (10m) | website | paper We provide our PyTorch implementation of unpaired image-to-image tra
Masked regression code - Masked Regression
Masked Regression MR - Python Implementation This repositery provides a python implementation of MR (Masked Regression). MR can efficiently synthesize
Py-faster-rcnn - Faster R-CNN (Python implementation)
py-faster-rcnn has been deprecated. Please see Detectron, which includes an implementation of Mask R-CNN. Disclaimer The official Faster R-CNN code (w
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
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
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
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
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
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
Much faster than SORT(Simple Online and Realtime Tracking), a little worse than SORT
QSORT QSORT(Quick + Simple Online and Realtime Tracking) is a simple online and realtime tracking algorithm for 2D multiple object tracking in video s
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
This repository for project that can Automate Number Plate Recognition (ANPR) in Morocco Licensed Vehicles. 💻 + 🚙 + 🇲🇦 = 🤖 🕵🏻♂️
MoroccoAI Data Challenge (Edition #001) This Reposotory is result of our work in the comepetiton organized by MoroccoAI in the context of the first Mo
Faster Twitch Alerts is a highly customizable, lightning-fast alternative to Twitch's slow mobile notification system
Faster Twitch Alerts What is "Faster Twitch Alerts"? Faster Twitch Alerts is a highly customizable, lightning-fast alternative to Twitch's slow mobile
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
A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN
A Pytorch Implementation of Source Data-free Domain Adaptation for a Faster R-CNN Please follow Faster R-CNN and DAF to complete the environment confi
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.
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
A tool to auto generate the basic mocks and asserts for faster unit testing
Mock Generator A tool to generate the basic mocks and asserts for faster unit testing. 🎉 New: you can now use pytest-mock-generator, for more fluid p
Faster, modernized fork of the language identification tool langid.py
py3langid py3langid is a fork of the standalone language identification tool langid.py by Marco Lui. Original license: BSD-2-Clause. Fork license: BSD
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
A Python package for faster, safer, and simpler ML processes
Bender 🤖 A Python package for faster, safer, and simpler ML processes. Why use bender? Bender will make your machine learning processes, faster, safe
Convex optimization for fun and profit.
CFMM Optimal Routing This repository contains the code needed to generate the figures used in the paper Optimal Routing for Constant Function Market M
🚢 Docker images and utilities to power your Python APIs and help you ship faster. With support for Uvicorn, Gunicorn, Starlette, and FastAPI.
🚢 inboard 🐳 Docker images and utilities to power your Python APIs and help you ship faster. Description This repository provides Docker images and a
Pyinstrument - a Python profiler. A profiler is a tool to help you optimize your code - make it faster.
Pyinstrument🚴 Call stack profiler for Python. Shows you why your code is slow!
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
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
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
wxPython's Project Phoenix. A new implementation of wxPython, better, stronger, faster than he was before.
wxPython Project Phoenix Introduction Welcome to wxPython's Project Phoenix! Phoenix is the improved next-generation wxPython, "better, stronger, fast
A bot written in python that send prefilled Google Forms. It supports multithreading for faster execution time.
GoogleFormsBot https://flassy.xyz https://github.com/Shawey/GoogleFormsBot Requirements: os (Default) ast (Default) threading (Default) configparser (
a wrapper around pytest for executing tests to look for test flakiness and runtime regression
bubblewrap a wrapper around pytest for assessing flakiness and runtime regressions a cs implementations practice project How to Run: First, install de
DANet for Tabular data classification/ regression.
Deep Abstract Networks A PyTorch code implemented for the submission DANets: Deep Abstract Networks for Tabular Data Classification and Regression. Do
The best solution of the Weather Prediction track in the Yandex Shifts challenge
yandex-shifts-weather The repository contains information about my solution for the Weather Prediction track in the Yandex Shifts challenge https://re
Faster RCNN pytorch windows
Faster-RCNN-pytorch-windows Faster RCNN implementation with pytorch for windows Open cmd, compile this comands: cd lib python setup.py build develop T
Flask pre-setup architecture. This can be used in any flask project for a faster and better project code structure.
Flask pre-setup architecture. This can be used in any flask project for a faster and better project code structure. All the required libraries are already installed easily to use in any big project.
Air Pollution Prediction System using Linear Regression and ANN
AirPollution Pollution Weather Prediction System: Smart Outdoor Pollution Monitoring and Prediction for Healthy Breathing and Living Publication Link:
[NeurIPS-2021] Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici
ROMP: Monocular, One-stage, Regression of Multiple 3D People, ICCV21
Monocular, One-stage, Regression of Multiple 3D People ROMP, accepted by ICCV 2021, is a concise one-stage network for multi-person 3D mesh recovery f
Simple API for UCI Machine Learning Dataset Repository (search, download, analyze)
A simple API for working with University of California, Irvine (UCI) Machine Learning (ML) repository Table of Contents Introduction About Page of the
[NeurIPS-2021] Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
Efficient Graph Similarity Computation - (EGSC) This repo contains the source code and dataset for our paper: Slow Learning and Fast Inference: Effici
Implementation of Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning
advantage-weighted-regression Implementation of Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning, by Peng et al. (
[NeurIPS'21] Projected GANs Converge Faster
[Project] [PDF] [Supplementary] [Talk] This repository contains the code for our NeurIPS 2021 paper "Projected GANs Converge Faster" by Axel Sauer, Ka
Parallel Latent Tree-Induction for Faster Sequence Encoding
FastTrees This repository contains the experimental code supporting the FastTrees paper by Bill Pung. Software Requirements Python 3.6, NLTK and PyTor
Predicting diabetes over a five year period using logistic regression and the Pima First-Nation dataset
Diabetes This script uses the Pima First Nations dataset to create a model to predict whether or not an individual will develop Diabetes Mellitus Type