Python Faster-Convex-Lipschitz-Regression Resources

Quasi-Recurrent Neural Network (QRNN) for PyTorch Updated to support multi-GPU environments via DataParallel - see the the multigpu_dataparallel.py ex

NeuralSymbolicRegressionThatScales Pytorch implementation and pretrained models for the paper "Neural Symbolic Regression That Scales", presented at I

A Faster Pytorch Implementation of Faster R-CNN Write at the beginning [05/29/2020] This repo was initaited about two years ago, developed as the firs

Tacotron 2 (without wavenet) PyTorch implementation of Natural TTS Synthesis By Conditioning Wavenet On Mel Spectrogram Predictions. This implementati

Human Pose Regression with Residual Log-likelihood Estimation [Paper] [arXiv] [Project Page] Human Pose Regression with Residual Log-likelihood Estima

Polarized Self-Attention: Towards High-quality Pixel-wise Regression This is an official implementation of: Huajun Liu, Fuqiang Liu, Xinyi Fan and Don

LARGE: Latent-Based Regression through GAN Semantics [Project Website] [Google Colab] [Paper] LARGE: Latent-Based Regression through GAN Semantics Yot

Licensing The majority of neural-scs is licensed under the CC BY-NC 4.0 License, however, portions of the project are available under separate license

Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx

GDR-Net This repo provides the PyTorch implementation of the work: Gu Wang, Fabian Manhardt, Federico Tombari, Xiangyang Ji. GDR-Net: Geometry-Guided

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

CloudAAE This is an tensorflow implementation of "CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Clouds" Files log:

Modeling distributions on Riemannian manifolds is a crucial component in understanding non-Euclidean data that arises, e.g., in physics and geology. The budding approaches in this space are limited by representational and computational tradeoffs. We propose and study a class of flows that uses convex potentials from Riemannian optimal transport. These are universal and can model distributions on any compact Riemannian manifold without requiring domain knowledge of the manifold to be integrated into the architecture. We demonstrate that these flows can model standard distributions on spheres, and tori, on synthetic and geological data.

Payment-Date-Prediction Machine Learning Model to predict the payment date of an invoice when it gets created in the system.

robotframework-stacktrace A listener for RF = 4.0 that prints a Stack Trace to console to faster find the code section where the failure appears. Ins

HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation Official PyTroch implementation of HPRNet. HPRNet: Hierarchical Point Regre

Delving into Deep Imbalanced Regression This repository contains the implementation code for paper: Delving into Deep Imbalanced Regression Yuzhe Yang

Self-Supervised Reward Regression (SSRR) Codebase for CoRL 2021 paper "Learning from Suboptimal Demonstration via Self-Supervised Reward Regression "

SparseML is a toolkit that includes APIs, CLIs, scripts and libraries that apply state-of-the-art sparsification algorithms such as pruning and quantization to any neural network. General, recipe-driven approaches built around these algorithms enable the simplification of creating faster and smaller models for the ML performance community at large.

This is the repository for The Python Workshop, published by Packt. It contains all the supporting project files necessary to work through the course from start to finish.

Code to run experiments in SLOE: A Faster Method for Statistical Inference in High-Dimensional Logistic Regression. Not an official Google product. Me

Easy-YT Making the process of downloading youtube videos faster and more convinient. What can it do? This python script can be used to download youtub

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

30 Days Of Machine Learning Using Pytorch Objective of the repository is to learn and build machine learning models using Pytorch. List of Algorithms

LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference This repository contains PyTorch evaluation code, training code and pretrained

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

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

Object detection and instance segmentation toolkit based on PaddlePaddle.

Parallelized symbolic regression built on Julia, and interfaced by Python. Uses regularized evolution, simulated annealing, and gradient-free optimization.

DiskCache is an Apache2 licensed disk and file backed cache library, written in pure-Python, and compatible with Django.

A tour through tensorflow with financial data I present several models ranging in complexity from simple regression to LSTM and policy networks. The s

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

Bottom-Up Human Pose Estimation Via Disentangled Keypoint Regression Introduction In this paper, we are interested in the bottom-up paradigm of estima

PyMAF This repository contains the code for the following paper: 3D Human Pose and Shape Regression with Pyramidal Mesh Alignment Feedback Loop Hongwe

celer Fast algorithm to solve Lasso-like problems with dual extrapolation. Currently, the package handles the following problems: Lasso weighted Lasso

lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con

SpeedTorch Faster pinned CPU tensor - GPU Pytorch variabe transfer and GPU tensor - GPU Pytorch variable transfer, in certain cases. Update 9-29-1

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

Yahoo! Finance market data downloader Ever since Yahoo! finance decommissioned their historical data API, many programs that relied on it to stop work

Open-L2O This repository establishes the first comprehensive benchmark efforts of existing learning to optimize (L2O) approaches on a number of proble

CDIoU-CDIoUloss CDIoU and CDIoU loss is like a convenient plug-in that can be used in multiple models. CDIoU and CDIoU loss have different excellent p

R2CNN_Faster_RCNN_Tensorflow Abstract This is a tensorflow re-implementation of R2CNN: Rotational Region CNN for Orientation Robust Scene Text Detecti

This is an oriented object detector based on tensorflow object detection API. Most of the code is not changed except for those related to the need of

RRD: Rotation-Sensitive Regression for Oriented Scene Text Detection For more details, please refer to our paper. Citing Please cite the related works

DewarpNet This repository contains the codes for DewarpNet training. Recent Updates [May, 2020] Added evaluation images and an important note about Ma

MMDetection is an open source object detection toolbox based on PyTorch. It is a part of the OpenMMLab project.

Trafalgar Python library to make development of portfolio analysis faster and easier Installation 🔥 For the moment, Trafalgar is still in beta develo

Welcome to gplearn! gplearn implements Genetic Programming in Python, with a scikit-learn inspired and compatible API. While Genetic Programming (GP)

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

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) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle

[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

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

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

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.

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

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

scandir, a better directory iterator and faster os.walk() scandir() is a directory iteration function like os.listdir(), except that instead of return

Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual

AWS DeepRacer Free Student Workshop: Run faster by using your custom waypoints Reward Function Template for waypoints def reward_function(params):

About statsmodels statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics an

Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible

Introduction neonrvm is an open source machine learning library for performing regression tasks using RVM technique. It is written in C programming la

Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree

Machine Learning From Scratch About Python implementations of some of the fundamental Machine Learning models and algorithms from scratch. The purpose

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

Machine Learning This project provides a web-interface, as well as a programmatic-api for various machine learning algorithms. Supported algorithms: S

Detecto is a Python package that allows you to build fully-functioning computer vision and object detection models with just 5 lines of code. Inferenc

Face Detection Docker Solution Using Faster R-CNN Dockerface is a deep learning face detector. It deploys a trained Faster R-CNN network on Caffe thro

Pyston is a faster and highly-compatible implementation of the Python programming language. Version 2 is currently closed source, but you can find the