3252 Repositories
Python time-series-data Libraries
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
Always know what to expect from your data.
Great Expectations Always know what to expect from your data. Introduction Great Expectations helps data teams eliminate pipeline debt, through data t
macOS development environment setup: Setting up a new developer machine can be an ad-hoc, manual, and time-consuming process.
dev-setup Motivation Setting up a new developer machine can be an ad-hoc, manual, and time-consuming process. dev-setup aims to simplify the process w
Jupyter notebook and datasets from the pandas Q&A video series
Python pandas Q&A video series Read about the series, and view all of the videos on one page: Easier data analysis in Python with pandas. Jupyter Note
Code and data accompanying Natural Language Processing with PyTorch
Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a
100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
100 pandas puzzles Puzzles notebook Solutions notebook Inspired by 100 Numpy exerises, here are 100* short puzzles for testing your knowledge of panda
FMA: A Dataset For Music Analysis
FMA: A Dataset For Music Analysis Michaël Defferrard, Kirell Benzi, Pierre Vandergheynst, Xavier Bresson. International Society for Music Information
This is a simple face recognition mini project that was completed by a team of 3 members in 1 week's time
PeekingDuckling 1. Description This is an implementation of facial identification algorithm to detect and identify the faces of the 3 team members Cla
Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.
Python for downloading model data (HRRR, RAP, GFS, NBM, etc.) from NOMADS, NOAA's Big Data Program partners (Amazon, Google, Microsoft), and the University of Utah Pando Archive System.
A High-Quality Real Time Upscaler for Anime Video
Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua
Predictive Modeling & Analytics on Home Equity Line of Credit
Predictive Modeling & Analytics on Home Equity Line of Credit Data (Python) HMEQ Data Set In this assignment we will use Python to examine a data set
Implements a fake news detection program using classifiers.
Fake news detection Implements a fake news detection program using classifiers for Data Mining course at UoA. Description The project is the categoriz
A collection of data structures and algorithms I'm writing while learning
Data Structures and Algorithms: This is a collection of data structures and algorithms that I write while learning the subject Stack: stack.py A stack
Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data
1 Meta-FDMIxup Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data. (ACM MM 2021) paper News! the rep
Code for "Multi-Time Attention Networks for Irregularly Sampled Time Series", ICLR 2021.
Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly
We simulate traveling back in time with a modern camera to rephotograph famous historical subjects.
[SIGGRAPH Asia 2021] Time-Travel Rephotography [Project Website] Many historical people were only ever captured by old, faded, black and white photos,
Script that allows to download data with satellite's orbit height and create CSV with their change in time.
Satellite orbit height ◾ Requirements Python = 3.8 Packages listen in reuirements.txt (run pip install -r requirements.txt) Account on Space Track ◾
A tool for RaceRoom Racing Experience which shows you launch data
R3E Launch Tool A tool for RaceRoom Racing Experience which shows you launch data. Usage Run the tool, change the Stop Speed to whatever you want, and
This is a web scraper, using Python framework Scrapy, built to extract data from the Deals of the Day section on Mercado Livre website.
Deals of the Day This is a web scraper, using the Python framework Scrapy, built to extract data such as price and product name from the Deals of the
A Simple Key-Value Data-store written in Python
mercury-db This is a File Based Key-Value Datastore that supports basic CRUD (Create, Read, Update, Delete) operations developed using Python. The dat
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment
To attract customers, the hotel chain has added to its website the ability to book a room without prepayment. We need to predict whether the customer is going to reject the booking or not. Since in case of refusal, the hotel incurs losses.
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
PyTorch GPU implementation of the ES-RNN model for time series forecasting
Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm A GPU-enabled version of the hybrid ES-RNN model by Slawek et al that won the M4 time-series
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav
Implementation of deep learning models for time series in PyTorch.
List of Implementations: Currently, the reimplementation of the DeepAR paper(DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks
Fully Convlutional Neural Networks for state-of-the-art time series classification
Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin
Practical Time-Series Analysis, published by Packt
Practical Time-Series Analysis This is the code repository for Practical Time-Series Analysis, published by Packt. It contains all the supporting proj
Machine Learning for Time-Series with Python.Published by Packt
Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am
Deep Learning for Time Series Classification
Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re
U-Time: A Fully Convolutional Network for Time Series Segmentation
U-Time & U-Sleep Official implementation of The U-Time [1] model for general-purpose time-series segmentation. The U-Sleep [2] model for resilient hig
Code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation
PiecewiseLinearTimeSeriesApproximation code from Daniel Lemire, A Better Alternative to Piecewise Linear Time Series Segmentation, SIAM Data Mining 20
Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.
Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re
A simple flask application to collect annotations for the Turing Change Point Dataset, a benchmark dataset for change point detection algorithms
AnnotateChange Welcome to the repository of the "AnnotateChange" application. This application was created to collect annotations of time series data
Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)
taganomaly Anomaly detection labeling tool, specifically for multiple time series (one time series per category). Taganomaly is a tool for creating la
Time series annotation library.
CrowdCurio Time Series Annotator Library The CrowdCurio Time Series Annotation Library implements classification tasks for time series. Features Suppo
The Wearables Development Toolkit - a development environment for activity recognition applications with sensor signals
Wearables Development Toolkit (WDK) The Wearables Development Toolkit (WDK) is a framework and set of tools to facilitate the iterative development of
TICC is a python solver for efficiently segmenting and clustering a multivariate time series
TICC TICC is a python solver for efficiently segmenting and clustering a multivariate time series. It takes as input a T-by-n data matrix, a regulariz
A Multipurpose Library for Synthetic Time Series Generation in Python
TimeSynth Multipurpose Library for Synthetic Time Series Please cite as: J. R. Maat, A. Malali, and P. Protopapas, “TimeSynth: A Multipurpose Library
Time should be taken seer-iously
TimeSeers seers - (Noun) plural form of seer - A person who foretells future events by or as if by supernatural means TimeSeers is an hierarchical Bay
Methods to get the probability of a changepoint in a time series.
Bayesian Changepoint Detection Methods to get the probability of a changepoint in a time series. Both online and offline methods are available. Read t
DeltaPy - Tabular Data Augmentation (by @firmai)
DeltaPy — Tabular Data Augmentation & Feature Engineering Finance Quant Machine Learning ML-Quant.com - Automated Research Repository Introduction T
A Python package for time series augmentation
tsaug tsaug is a Python package for time series augmentation. It offers a set of augmentation methods for time series, as well as a simple API to conn
An example of time series augmentation methods with Keras
Time Series Augmentation This is a collection of time series data augmentation methods and an example use using Keras. News 2020/04/16: Repository Cre
🏹 Better dates & times for Python
Arrow: Better dates & times for Python Arrow is a Python library that offers a sensible and human-friendly approach to creating, manipulating, formatt
A Time Series Library for Apache Spark
Flint: A Time Series Library for Apache Spark The ability to analyze time series data at scale is critical for the success of finance and IoT applicat
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
Supervised forecasting of sequential data in Python.
Supervised forecasting of sequential data in Python. Intro Supervised forecasting is the machine learning task of making predictions for sequential da
Library for time-series-forecasting-as-a-service.
TIMEX TIMEX (referred in code as timexseries) is a framework for time-series-forecasting-as-a-service. Its main goal is to provide a simple and generi
Python implementation of the Learning Time-Series Shapelets method, that learns a shapelet-based time-series classifier with gradient descent.
shaplets Python implementation of the Learning Time-Series Shapelets method by Josif Grabocka et al., that learns a shapelet-based time-series classif
Whisper is a file-based time-series database format for Graphite.
Whisper Overview Whisper is one of three components within the Graphite project: Graphite-Web, a Django-based web application that renders graphs and
Algorithms for outlier, adversarial and drift detection
Alibi Detect is an open source Python library focused on outlier, adversarial and drift detection. The package aims to cover both online and offline d
Automated Time Series Forecasting
AutoTS AutoTS is a time series package for Python designed for rapidly deploying high-accuracy forecasts at scale. There are dozens of forecasting mod
catch-22: CAnonical Time-series CHaracteristics
catch22 - CAnonical Time-series CHaracteristics About catch22 is a collection of 22 time-series features coded in C that can be run from Python, R, Ma
Machine Learning Time-Series Platform
cesium: Open-Source Platform for Time Series Inference Summary cesium is an open source library that allows users to: extract features from raw time s
Python port of R's Comprehensive Dynamic Time Warp algorithm package
Welcome to the dtw-python package Comprehensive implementation of Dynamic Time Warping algorithms. DTW is a family of algorithms which compute the loc
An API-first distributed deployment system of deep learning models using timeseries data to analyze and predict systems behaviour
Gordo Building thousands of models with timeseries data to monitor systems. Table of content About Examples Install Uninstall Developer manual How to
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
:spaghetti: Pastas is an open-source Python framework for the analysis of hydrological time series.
Pastas: Analysis of Groundwater Time Series Pastas: what is it? Pastas is an open source python package for processing, simulating and analyzing groun
(JMLR' 19) A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin
Forecast dynamically at scale with this unique package. pip install scalecast
🌄 Scalecast: Dynamic Forecasting at Scale About This package uses a scaleable forecasting approach in Python with common scikit-learn and statsmodels
Hierarchical Time Series Forecasting with a familiar API
scikit-hts Hierarchical Time Series with a familiar API. This is the result from not having found any good implementations of HTS on-line, and my work
Quantify the difference between two arbitrary curves in space
similaritymeasures Quantify the difference between two arbitrary curves Curves in this case are: discretized by inidviudal data points ordered from a
A python library for time-series smoothing and outlier detection in a vectorized way.
tsmoothie A python library for time-series smoothing and outlier detection in a vectorized way. Overview tsmoothie computes, in a fast and efficient w
An open source python library for automated feature engineering
"One of the holy grails of machine learning is to automate more and more of the feature engineering process." ― Pedro Domingos, A Few Useful Things to
An intuitive library to extract features from time series
Time Series Feature Extraction Library Intuitive time series feature extraction This repository hosts the TSFEL - Time Series Feature Extraction Libra
Time series changepoint detection
changepy Changepoint detection in time series in pure python Install pip install changepy Examples from changepy import pelt from cha
The Turing Change Point Detection Benchmark: An Extensive Benchmark Evaluation of Change Point Detection Algorithms on real-world data
Turing Change Point Detection Benchmark Welcome to the repository for the Turing Change Point Detection Benchmark, a benchmark evaluation of change po
Highly comparative time-series analysis
〰️ hctsa 〰️ : highly comparative time-series analysis hctsa is a software package for running highly comparative time-series analysis using Matlab (fu
Python binding for Khiva library.
Khiva-Python Build Documentation Build Linux and Mac OS Build Windows Code Coverage README This is the Khiva Python binding, it allows the usage of Kh
Timeseries analysis for neuroscience data
=================================================== Nitime: timeseries analysis for neuroscience data ===============================================
Python package for dynamic system estimation of time series
PyDSE Toolset for Dynamic System Estimation for time series inspired by DSE. It is in a beta state and only includes ARMA models right now. Documentat
A Python library for unevenly-spaced time series analysis
traces A Python library for unevenly-spaced time series analysis. Why? Taking measurements at irregular intervals is common, but most tools are primar
An LSTM for time-series classification
Update 10-April-2017 And now it works with Python3 and Tensorflow 1.1.0 Update 02-Jan-2017 I updated this repo. Now it works with Tensorflow 0.12. In
WTTE-RNN a framework for churn and time to event prediction
WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p
Python package for downloading ECMWF reanalysis data and converting it into a time series format.
ecmwf_models Readers and converters for data from the ECMWF reanalysis models. Written in Python. Works great in combination with pytesmo. Citation If
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
FADNet++: Real-Time and Accurate Disparity Estimation with Configurable Networks
Where-Got-Time - An NUS timetable generator which uses a genetic algorithm to optimise timetables to suit the needs of NUS students
Where Got Time(table)? A timetable optimsier which uses an evolutionary algorith
A way of looking at COVID-19 data that I haven't seen before.
Visualizing Omicron: COVID-19 Deaths vs. Cases Click here for other countries. Data is from Our World in Data/Johns Hopkins University. About this pro
Analyzed the data of VISA applicants to build a predictive model to facilitate the process of VISA approvals.
Analyzed the data of Visa applicants, built a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommended a suitable profile for the applicants for whom the visa should be certified or denied.
Medical appointments No-Show classifier
Medical Appointments No-shows Why do 20% of patients miss their scheduled appointments? A person makes a doctor appointment, receives all the instruct
Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máquina.
Estatistica para Ciência de Dados e Machine Learning Arquivos do curso online sobre a estatística voltada para ciência de dados e aprendizado de máqui
Prometheus Exporter for data scraped from datenplattform.darmstadt.de
darmstadt-opendata-exporter Scrapes data from https://datenplattform.darmstadt.de and presents it in the Prometheus Exposition format. Pull requests w
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort
PyTorch EO aims to make Deep Learning for Earth Observation data easy and accessible to real-world cases and research alike.
Pytorch EO Deep Learning for Earth Observation applications and research. 🚧 This project is in early development, so bugs and breaking changes are ex
A web application that provides real time temperature and humidity readings of a house.
About A web application which provides real time temperature and humidity readings of a house. If you're interested in the data collected so far click
Full-Stack application that visualizes amusement park safety.
Amusement Park Ride Safety Analysis Project Proposal We have chosen to look into amusement park data to explore ride safety relationships visually, in
A ULauncher/Albert extension that supports currency, units and date time conversion, as well as a calculator that supports complex numbers and functions.
Ulauncher/Albert Calculate Anything Ulauncher/Albert Calculate Anything is an extension for Ulauncher and Albert to calculate things like currency, ti
Datasets, tools, and benchmarks for representation learning of code.
The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided
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 (
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
Data Science 45-min Intros Every week*, our data science team @Gnip (aka @TwitterBoulder) gets together for about 50 minutes to learn something. While
A middle-to-high level algorithm book designed with coding interview at heart!
Hands-on Algorithmic Problem Solving A one-stop coding interview prep book! About this book In short, this is a middle-to-high level algorithm book de
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
Here are the sections: Data Science Cheatsheets Data Science EBooks Data Science Question Bank Data Science Case Studies Data Science Portfolio Data J
A site that displays up to date COVID-19 stats, powered by fastpages.
https://covid19dashboards.com This project was built with fastpages Background This project showcases how you can use fastpages to create a static das
Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks
Spark Python Notebooks This is a collection of IPython notebook/Jupyter notebooks intended to train the reader on different Apache Spark concepts, fro
🤖 ⚡ scikit-learn tips
🤖 ⚡ scikit-learn tips New tips are posted on LinkedIn, Twitter, and Facebook. 👉 Sign up to receive 2 video tips by email every week! 👈 List of all
A series of Jupyter notebooks with Chinese comment that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
Hands-on-Machine-Learning 目的 这份笔记旨在帮助中文学习者以一种较快较系统的方式入门机器学习, 是在学习Hands-on Machine Learning with Scikit-Learn and TensorFlow这本书的 时候做的个人笔记: 此项目的可取之处 原书的
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
HackerMath for Machine Learning “Study hard what interests you the most in the most undisciplined, irreverent and original manner possible.” ― Richard
List of papers, code and experiments using deep learning for time series forecasting
Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch
Jupyter Notebook tutorials on solving real-world problems with Machine Learning & Deep Learning using PyTorch. Topics: Face detection with Detectron 2, Time Series anomaly detection with LSTM Autoencoders, Object Detection with YOLO v5, Build your first Neural Network, Time Series forecasting for Coronavirus daily cases, Sentiment Analysis with BERT.
Koç University deep learning framework.
Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU