240 Repositories
Python kernel-ridge-regression Libraries
Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch
30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Implementation of different ML Algorithms from scratch, written in Python 3.x
Implementation of different ML Algorithms from scratch, written in Python 3.x
A scikit-learn-compatible module for estimating prediction intervals.
|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn
Simple, fast, and parallelized symbolic regression in Python/Julia via regularized evolution and simulated annealing
Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.
A resource for learning about deep learning techniques from regression to LSTM and Reinforcement Learning using financial data and the fitness functions of algorithmic trading
A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
This is an official implementation of our CVPR 2021 paper "Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression" (https://arxiv.org/abs/2104.02300)
Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression Introduction In this paper, we are interested in the bottom-up paradigm of estima
(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int
Code for "3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop"
PyMAF This repository contains the code for the following paper: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop Hongwe
Fast solver for L1-type problems: Lasso, sparse Logisitic regression, Group Lasso, weighted Lasso, Multitask Lasso, etc.
celer Fast algorithm to solve Lasso-like problems with dual extrapolation. Currently, the package handles the following problems: Lasso weighted Lasso
Large-scale linear classification, regression and ranking in Python
lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con
A unified framework for machine learning with time series
Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible
Code for Mesh Convolution Using a Learned Kernel Basis
Mesh Convolution This repository contains the implementation (in PyTorch) of the paper FULLY CONVOLUTIONAL MESH AUTOENCODER USING EFFICIENT SPATIALLY
RRD: Rotation-Sensitive Regression for Oriented Scene Text Detection
RRD: Rotation-Sensitive Regression for Oriented Scene Text Detection For more details, please refer to our paper. Citing Please cite the related works
Code for the paper "DewarpNet: Single-Image Document Unwarping With Stacked 3D and 2D Regression Networks" (ICCV '19)
DewarpNet This repository contains the codes for DewarpNet training. Recent Updates [May, 2020] Added evaluation images and an important note about Ma
Genetic Programming in Python, with a scikit-learn inspired API
Welcome to gplearn! gplearn implements Genetic Programming in Python, with a scikit-learn inspired and compatible API. While Genetic Programming (GP)
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
ThunderSVM: A Fast SVM Library on GPUs and CPUs
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
mlpack: a scalable C++ machine learning library --
a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
ThunderSVM: A Fast SVM Library on GPUs and CPUs
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
Fast and Easy Infinite Neural Networks in Python
Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural
mlpack: a scalable C++ machine learning library --
a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual
A Python interface module to the SAS System. It works with Linux, Windows, and mainframe SAS. It supports the sas_kernel project (a Jupyter Notebook kernel for SAS) or can be used on its own.
A Python interface to MVA SAS Overview This module creates a bridge between Python and SAS 9.4. This module enables a Python developer, familiar with
Statsmodels: statistical modeling and econometrics in Python
About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an
A unified framework for machine learning with time series
Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible
An open source machine learning library for performing regression tasks using RVM technique.
Introduction neonrvm is an open source machine learning library for performing regression tasks using RVM technique. It is written in C programming la
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose
Simple machine learning library / 簡單易用的機器學習套件
FukuML Simple machine learning library / 簡單易用的機器學習套件 Installation $ pip install FukuML Tutorial Lesson 1: Perceptron Binary Classification Learning Al
Web-interface + rest API for classification and regression (https://jeff1evesque.github.io/machine-learning.docs)
Machine Learning This project provides a web-interface, as well as a programmatic-api for various machine learning algorithms. Supported algorithms: S