1227 Repositories
Python series-analysis Libraries
ALSPAC data analysis studying links between screen-usage and mental health issues in children. Provided data has been synthesised.
ADSMH - Mental Health and Screen Time Group coursework for Applied Data Science at the University of Bristol. Overview The data set that you have was
El Niño - Southern Oscillation analysis compared to minimum flow rates of rivers in northeast Brazil
ENSO (El Niño - Southern Oscillation) analysis in northeast Brazil É comprovada a influência dos fenômenos El Niño e La Niña nas secas no nordesde bra
EchoDNS - Analyze your DNS traffic super easy, shows all requested DNS traffic
EchoDNS - Analyze your DNS traffic super easy, shows all requested DNS traffic
This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures using receptive field analysis (RFA) and create graph visualizations of your architecture.
ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin
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
ioztat is a storage load analysis tool for OpenZFS
ioztat is a storage load analysis tool for OpenZFS. It provides iostat-like statistics at an individual dataset/zvol level.
A Python Bytecode Disassembler helping reverse engineers in dissecting Python binaries
A Python Bytecode Disassembler helping reverse engineers in dissecting Python binaries by disassembling and analyzing the compiled python byte-code(.pyc) files across all python versions (including Python 3.10.*)
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
PyPortfolioOpt has recently been published in the Journal of Open Source Software 🎉 PyPortfolioOpt is a library that implements portfolio optimizatio
Practical Machine Learning with Python
Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.
Semi-Automated Data Processing
Perform semi automated exploratory data analysis, feature engineering and feature selection on provided dataset by visualizing every possibilities on each step and assisting the user to make a meaningful decision to achieve a low-bias and low-variance model.
Security audit Python project dependencies against security advisory databases.
Security audit Python project dependencies against security advisory databases.
Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle.
2019-indian-election-eda Exploratory Data Analysis of the 2019 Indian General Elections using a dataset from Kaggle. This project is a part of the Cou
API Server for VoIP analysis (CDR + Audio CODECs)
Swagger generated server Overview This server was generated by the swagger-codegen project. By using the OpenAPI-Spec from a remote server, you can ea
AB-test-analyzer - Python class to perform AB test analysis
AB-test-analyzer Python class to perform AB test analysis Overview This repo con
Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products
Contains analysis of trends from Fitbit Dataset (source: Kaggle) to see how the trends can be applied to Bellabeat customers and Bellabeat products.
Repo for The Crown: Exploratory Analysis of Nim Malware DEF CON 615 talk
Repo for "The Crown: Exploratory Analysis of Nim Malware" DEF CON 615 talk
Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis
Introduction This is an implementation of our paper Supervised 3D Pre-training on Large-scale 2D Natural Image Datasets for 3D Medical Image Analysis.
[SDM 2022] Towards Similarity-Aware Time-Series Classification
SimTSC This is the PyTorch implementation of SDM2022 paper Towards Similarity-Aware Time-Series Classification. We propose Similarity-Aware Time-Serie
HuSpaCy: industrial-strength Hungarian natural language processing
HuSpaCy: Industrial-strength Hungarian NLP HuSpaCy is a spaCy model and a library providing industrial-strength Hungarian language processing faciliti
R-package accompanying the paper "Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction"
dffm The goal of dffm is to provide functionality to apply the methods developed in the paper “Dynamic Factor Model for Functional Time Series: Identi
Repository for the AugmentedPCA Python package.
Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that
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
A framework for multi-step probabilistic time-series/demand forecasting models
JointDemandForecasting.py A framework for multi-step probabilistic time-series/demand forecasting models File stucture JointDemandForecasting contains
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data
FEMDA: Robust classification with Flexible Discriminant Analysis in heterogeneous data. Flexible EM-Inspired Discriminant Analysis is a robust supervised classification algorithm that performs well in noisy and contaminated datasets.
Active Transport Analytics Model: A new strategic transport modelling and data visualization framework
{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”
Active Transport Analytics Model (ATAM) is a new strategic transport modelling and data visualization framework for Active Transport as well as emerging micro-mobility modes
{ATAM} Active Transport Analytics Model Active Transport Analytics Model (“ATAM”) is a new strategic transport modelling and data visualization framew
Sentinel-1 SAR time series analysis for OSINT use
SARveillance Sentinel-1 SAR time series analysis for OSINT use. Description Generates a time lapse GIF of the Sentinel-1 satellite images for the loca
People tracker on the Internet: OSINT analysis and research tool by Jose Pino
trape (stable) v2.0 People tracker on the Internet: Learn to track the world, to avoid being traced. Trape is an OSINT analysis and research tool, whi
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
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
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
Python library for the analysis of dynamic measurements
Python library for the analysis of dynamic measurements The goal of this library is to provide a starting point for users in metrology and related are
Streamlit App For Product Analysis - Streamlit App For Product Analysis
Streamlit_App_For_Product_Analysis Здравствуйте! Перед вами дашборд, позволяющий
Delta Conformity Sociopatterns Analysis - Delta Conformity Sociopatterns Analysis
Delta_Conformity_Sociopatterns_Analysis ∆-Conformity is a local homophily measur
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
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
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
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
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
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
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 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
Technical Analysis library in pandas for backtesting algotrading and quantitative analysis
bta-lib - A pandas based Technical Analysis Library bta-lib is pandas based technical analysis library and part of the backtrader family. Links Main P
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
This is a Python wrapper for TA-LIB based on Cython instead of SWIG.
TA-Lib This is a Python wrapper for TA-LIB based on Cython instead of SWIG. From the homepage: TA-Lib is widely used by trading software developers re
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
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
Software Engineer Salary Prediction
Based on 2021 stack overflow data, this machine learning web application helps one predict the salary based on years of experience, level of education and the country they work in.
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
A general and strong 3D object detection codebase that supports more methods, datasets and tools (debugging, recording and analysis).
ALLINONE-Det ALLINONE-Det is a general and strong 3D object detection codebase built on OpenPCDet, which supports more methods, datasets and tools (de
Finite Element Analysis
FElupe - Finite Element Analysis FElupe is a Python 3.6+ finite element analysis package focussing on the formulation and numerical solution of nonlin
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 (
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
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
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
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.
A Practitioner's Guide to Natural Language Processing
Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, Text Analytics with Python published by Apress/Springer.
A powerful and user-friendly binary analysis platform!
angr angr is a platform-agnostic binary analysis framework. It is brought to you by the Computer Security Lab at UC Santa Barbara, SEFCOM at Arizona S
Anomaly detection related books, papers, videos, and toolboxes
Anomaly Detection Learning Resources Outlier Detection (also known as Anomaly Detection) is an exciting yet challenging field, which aims to identify
Dshell is a network forensic analysis framework.
Dshell An extensible network forensic analysis framework. Enables rapid development of plugins to support the dissection of network packet captures. K
Free and open source qualitative research tool
Taguette A spin on the phrase "tag it!", Taguette is a free and open source qualitative research tool that allows users to: Import PDFs, Word Docs (.d
Resco: A simple python package that report the effect of deep residual learning
resco Description resco is a simple python package that report the effect of dee
Customer Service Requests Analysis is one of the practical life problems that an analyst may face. This Project is one such take. The project is a beginner to intermediate level project. This repository has a Source Code, README file, Dataset, Image and License file.
Customer Service Requests Analysis Project 1 DESCRIPTION Background of Problem Statement : NYC 311's mission is to provide the public with quick and e
Analysis of a daily word game "Wordle"
Wordle Analysis of a daily word game "Wordle" https://www.powerlanguage.co.uk/wordle/ Description Worlde is a daily word game in which a player attemp