Python Training-data-storage Resources

English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc

FAIMED 3D use fastai to quickly train fully three-dimensional models on radiological data Classification from faimed3d.all import * Load data in vari

fast.ai ULMFiT with SentencePiece from pretraining to deployment Motivation: Why even bother with a non-BERT / Transformer language model? Short answe

Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models

An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for Trans

Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF

Project5-Data-processing-system User just needed to copy both these file to a folder and open Project5.py using cmd or using any python ide. It is to

zEpid zEpid is an epidemiology analysis package, providing easy to use tools for epidemiologists coding in Python 3.5+. The purpose of this library is

Explorative Data Analysis Get data into a usable format! Find out if the following predictive modeling phase will be successful! Combine everything in

cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear

Impyute is a library of missing data imputation algorithms. This library was designed to be super lightweight, here's a sneak peak at what impyute can do.

Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.

Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex

dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.

Pypeln Pypeln (pronounced as "pypeline") is a simple yet powerful Python library for creating concurrent data pipelines. Main Features Simple: Pypeln

Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and

Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm

MCML is a toolkit for semi-supervised dimensionality reduction and quantitative analysis of Multi-Class, Multi-Label data. We demonstrate its use

Dump Data from FTDI Serial Port to Binary File on MacOS

Crypto Stats and Tweets Data Pipeline using Airflow Introduction Project Overview This project was brought upon through Udacity's nanodegree program.

trRosetta This package is a part of trRosetta protein structure prediction protocol developed in: Improved protein structure prediction using predicte

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear

68 keypoint annotations for COFW test data This repository contains manually annotated 68 keypoints for COFW test data (original annotation of CFOW da

Whale Demo Instance: Bigquery Public Data This is a fully-functioning demo instance of the whale data catalog, actively scraping data from Bigquery's

FFT-accelerated Interpolation-based t-SNE (FIt-SNE) Introduction t-Stochastic Neighborhood Embedding (t-SNE) is a highly successful method for dimensi

Code for an interactive UMAP visualization of the MNIST data set. Demo at https://grantcuster.github.io/umap-explorer/. You can read more about the de

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc

livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A

Visualization of the Austrian Monuments Visualization of the monument landscape of the austrian monuments registry (Bundesdenkmalamt Denkmalverzeichni

Falcon: Interactive Visual Analysis for Big Data Crossfilter millions of records without latencies. This project is work in progress and not documente

Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To

Make Complex Heatmaps Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. H

Colorcet: Collection of perceptually uniform colormaps Build Status Coverage Latest dev release Latest release Docs What is it? Colorcet is a collecti

Welcome to Streamlit 👋 The fastest way to build and share data apps. Streamlit lets you turn data scripts into sharable web apps in minutes, not week

Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome

Visdom A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Python. Overview Concepts Setup Usage API To

Sample Analytics In large-scale surveys, often complex random mechanisms are used to select samples. Estimates derived from such samples must reflect

Datashader is a data rasterization pipeline for automating the process of creating meaningful representations of large amounts of data.

An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu

Nuance I use Nuance to curate varied visualization thoughts during my data scientist career. It is not yet a package but a list of small ideas. Welcom

🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams

Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).

Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.

A program that analyzes data from inertia measurement units installeed in aircraft and generates g-exceedance curves

Distributed Arcface Training in Pytorch

Mesa: A Memory-saving Training Framework for Transformers This is the official PyTorch implementation for Mesa: A Memory-saving Training Framework for

radiale what if home-automation was also homoiconic? The upper or proximal row contains three bones, to which Gegenbaur has applied the terms radiale,

Byte Steganography Image/Data Injector. For artists or people to inject their own print/data into their images. TODO Add more file formats to support.

dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu

Facebook Scraper Use Flask API to wrap Facebook data. Grab the wapper of Facebook public pages without an API key. (Currently working 2021) Setup Befo

Stock and Index Beta Calculator Python script that calculates the beta (β) of a stock against the chosen index. The script retrieves the data and resa

accsr This lightweight library contains utilities for managing, loading, uploading, opening and generally wrangling data and configurations. It was ba

BENDR BErt-like Neurophysiological Data Representation This repository contains the source code for reproducing, or extending the BERT-like self-super

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

The pure and clear PyTorch Distributed Training Framework. Introduction Requirements and Usage Dependency Dataset Basic Usage Slurm Cluster Usage Base

ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T

Factorisation-based Image Labelling Overview This is a scheme for training and applying the factorisation-based image labelling (FIL) framework. Some

Rainbow 🌈 An implementation of Rainbow DQN which outperforms the paper's (Hessel et al. 2017) results on 40% of tested games while using 20x less dat

Deep Learning with PyTorch made easy 🚀 ! Carefree? carefree-learn aims to provide CAREFREE usages for both users and developers. It also provides a c

YOLOv4 CrowdHuman Tutorial This is a tutorial demonstrating how to train a YOLOv4 people detector using Darknet and the CrowdHuman dataset. Table of c

MIDASpy Overview MIDASpy is a Python package for multiply imputing missing data using deep learning methods. The MIDASpy algorithm offers significant

sqliteBasics create a database, insert data and easily select it with Sqlite Watch on YouTube a step by step tutorial explaining this code: https://yo

insilico: A Python package to process & model ChEMBL data. ChEMBL is a manually curated chemical database of bioactive molecules with drug-like proper

foamTEX An open source utility for creating publication quality LaTex figures generated from OpenFOAM data files. Explore the docs » Report Bug · Requ

DBMS project- Hotel Franchise Data and application project By TEAM Kurukunda Bhargavi Pamulapati Pallavi Greeshma Amaraneni What is this project about

Sheet Data Image/PDF-to-CSV Converter

Code for "Training Neural Networks with Fixed Sparse Masks" (NeurIPS 2021).

Restormer: Efficient Transformer for High-Resolution Image Restoration Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan,

'db' within pydantic - A single model for shaping, creating, accessing, storing data within a Database Key Features Integrated Redis Caching Support A

This is a tool to help you quickly solve classification problems including: data analysis, training, report results and model explanation.

datasketch: Big Data Looks Small datasketch gives you probabilistic data structures that can process and search very large amount of data super fast,

AugMix Introduction We propose AugMix, a data processing technique that mixes augmented images and enforces consistent embeddings of the augmented ima

How to use TensorLayer While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLay

HiddenLayer A lightweight library for neural network graphs and training metrics for PyTorch, Tensorflow, and Keras. HiddenLayer is simple, easy to ex

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Youtube video details analyser Steps to run this project Please set the AuthKey which you can fetch from google developer console and paste it in the

zeus is a Python implementation of the Ensemble Slice Sampling method. Fast & Robust Bayesian Inference, Efficient Markov Chain Monte Carlo (MCMC), Bl

Face Recognition: Too Bias, or Not Too Bias? Robinson, Joseph P., Gennady Livitz, Yann Henon, Can Qin, Yun Fu, and Samson Timoner. "Face recognition:

Linear regression for data with measurement errors and intrinsic scatter (BCES) Python module for performing robust linear regression on (X,Y) data po

SageMaker Python SDK SageMaker Python SDK is an open source library for training and deploying machine learning models on Amazon SageMaker. With the S

Projeto: Machine Learning: Linguagens de Programacao 2004-2001 Projeto de Data Science e Machine Learning de análise de linguagens de programação de 2

Predicting Yelp Review Quality Table of Contents Introduction Motivation Goal and Central Questions The Data Data Storage and ETL EDA Data Pipeline Da

MIT Deep Learning This repository is a collection of tutorials for MIT Deep Learning courses. More added as courses progress. Tutorial: Deep Learning

Python Business Analytics Also instead of "watching" you can join the link-letter, it's already being sent out to about 90 people and you are free to

Python Data Science Handbook This repository contains the entire Python Data Science Handbook, in the form of (free!) Jupyter notebooks. How to Use th

Design and build a wrapper for the Open Weather API current weather data service that returns a city's temperature, with caching, also allowing for the temperature of the latest queried cities that are still validly cached to be retrieved.

By Investors, For Investors. Want to read this in Chinese? Click here Empyrial is a Python-based open-source quantitative investment library dedicated

Clinica Software platform for clinical neuroimaging studies Homepage | Documentation | Paper | Forum | See also: AD-ML, AD-DL ClinicaDL About The Proj

Front-end View Backend View Table of Contents Description Prerequisites Running Basic Information Measurements User Interface Feedback and usage Descr

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

Continuous Machine Learning project integration with DVC Data Version Control or DVC is an open-source tool for data science and machine learning proj

Trading Tesla with Machine Learning and Sentiment Analysis An interactive program to train a Random Forest Classifier to predict Tesla daily prices us

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

PyExplainer PyExplainer is a local rule-based model-agnostic technique for generating explanations (i.e., why a commit is predicted as defective) of J

AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-

Create postgres tables from CSV files This first section is only relate to creating tables from CSV files using postgres container alone. Just one of

For specific function. For my own convenience. Remind owner to share data to another DITO user.