Python Machine-Learning-for-Time-Series-with-Python Resources

Data Loader Plugin - Python Table of Content (ToC) Data Loader Plugin - Python Table of Content (ToC) Overview References Python module Python virtual

Salad Salad is an Open Source Python library to segment tissues into different biologically relevant regions based on Hidden Markov Random Fields. The

i3screens A helper tool for managing i3wm workspaces on multiple monitors. Use-case You have a multi-monitor setup and want to have the "same" workspa

No support is going to be provided of any kind, only maintaining this for vps user on request. This is a Telegram Bot written in Python for mirroring

💠 Discord-Online-Account-Forever Discord Online Account Forever 📸 Tutorial Token Discord NEVER SHARE YOUR TOKEN Installation Replit 🧿 Replit : Here

Python-based proof-of-concept tool for generating payloads that utilize unsafe Java object deserialization.

Python-ddos-bot Coded by Lamp#1442 A discord bot can stress ip addresses with python tool. Warning! DOS or DDOS is illegal, i shared for educational p

PyAF (Python Automatic Forecasting) PyAF is an Open Source Python library for Automatic Forecasting built on top of popular data science python module

Introduction MASS allows you to search a time series for a subquery resulting in an array of distances. These array of distances enable you to identif

ObsPy is an open-source project dedicated to provide a Python framework for processing seismological data. It provides parsers for common file formats

RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019) This repository contains python (3.5.2) implementation of

time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f

NOTE: sktime-dl is currently being updated to work correctly with sktime 0.6, and wwill be fully relaunched over the summer. The plan is Refactor and

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

A hands-off Anomaly Detection Library Table of contents What is Luminaire Quick Start Time Series Outlier Detection Workflow Anomaly Detection for Hig

TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini

findatapy findatapy creates an easy to use Python API to download market data from many sources including Quandl, Bloomberg, Yahoo, Google etc. using

Eiten - Algorithmic Investing Strategies for Everyone Eiten is an open source toolkit by Tradytics that implements various statistical and algorithmic

QuantStats: Portfolio analytics for quants QuantStats Python library that performs portfolio profiling, allowing quants and portfolio managers to unde

scikit-survival scikit-survival is a Python module for survival analysis built on top of scikit-learn. It allows doing survival analysis while utilizi

Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions. There is a lot more info if you head over to the documentation. You can also take a look at this blog post about Convoys.

PySurvival What is Pysurvival ? PySurvival is an open source python package for Survival Analysis modeling - the modeling concept used to analyze or p

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

Banpei Banpei is a Python package of the anomaly detection. Anomaly detection is a technique used to identify unusual patterns that do not conform to

Telemanom (v2.0) v2.0 updates: Vectorized operations via numpy Object-oriented restructure, improved organization Merge branches into single branch fo

slim-python is a package to learn customized scoring systems for decision-making problems. These are simple decision aids that let users make yes-no p

Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI

Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t

pymc-learn: Practical Probabilistic Machine Learning in Python Contents: Github repo What is pymc-learn? Quick Install Quick Start Index What is pymc-

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

LOFO (Leave One Feature Out) Importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, with a validation scheme of choice, based on the chosen metric.

partial_dependence A python library for plotting partial dependence patterns of machine learning classifiers. The technique is a black box approach to

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.

InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig

AdaNet is a lightweight TensorFlow-based framework for automatically learning high-quality models with minimal expert intervention. AdaNet buil

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn

CVXPY The CVXPY documentation is at cvxpy.org. We are building a CVXPY community on Discord. Join the conversation! For issues and long-form discussio

blackbox: A Python module for parallel optimization of expensive black-box functions What is this? A minimalistic and easy-to-use Python module that e

Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

Optuna: A hyperparameter optimization framework Website | Docs | Install Guide | Tutorial Optuna is an automatic hyperparameter optimization software

BBopt BBopt aims to provide the easiest hyperparameter optimization you'll ever do. Think of BBopt like Keras (back when Theano was still a thing) for

Dragonfly is an open source python library for scalable Bayesian optimisation. Bayesian optimisation is used for optimising black-box functions whose

River is a Python library for online machine learning. It is the result of a merger between creme and scikit-multiflow. River's ambition is to be the go-to library for doing machine learning on streaming data.

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

Alpha Zero General (any game, any framework!) A simplified, highly flexible, commented and (hopefully) easy to understand implementation of self-play

A tool that updates all your project's Python dependency files through Pull Requests on GitHub/GitLab. About This repo contains the bot that is runnin

Donkeycar is minimalist and modular self driving library for Python. It is developed for hobbyists and students with a focus on allowing fast experimentation and easy community contributions.

Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta

This is a collection of python modules that interact with the Ryze Tello drone.

m2cgen (Model 2 Code Generator) - is a lightweight library which provides an easy way to transpile trained statistical models into a native code

sklearn-porter Transpile trained scikit-learn estimators to C, Java, JavaScript and others. It's recommended for limited embedded systems and critical

ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi

Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi

Dagster An orchestration platform for the development, production, and observation of data assets. Dagster lets you define jobs in terms of the data f

Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co

Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow

unyt A package for handling numpy arrays with units. Often writing code that deals with data that has units can be confusing. A function might return

Machine Learning Videos This is a collection of recorded talks at machine learning conferences, workshops, seminars, summer schools, and miscellaneous

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Data Science Cheatsheets List of Data Science Cheatsheets to rule the world. Table of Contents Business Science Business Science Problem Framework Dat

EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num

Fast and customizable vulnerability scanner For JIRA. 🤔 What is this? Jira-Lens 🔍 is a Python Based vulnerability Scanner for JIRA. Jira is a propri

An open access book on scientific visualization using python and matplotlib

GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler

PortraitNet Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device". @ CAD&Graphics 2019 Introduction We propose a

PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to

DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48

Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image

UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc

TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under

Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s

Real-time Semantic Segmentation Comparative Study The repository contains the official TensorFlow code used in our papers: RTSEG: REAL-TIME SEMANTIC S

Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel

MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-

Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the

DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement

PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+

Real-Time Semantic Segmentation in TensorFlow Perform pixel-wise semantic segmentation on high-resolution images in real-time with Image Cascade Netwo

ICNet_tensorflow This repo provides a TensorFlow-based implementation of paper "ICNet for Real-Time Semantic Segmentation on High-Resolution Images,"

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

ICNet for Real-Time Semantic Segmentation on High-Resolution Images by Hengshuang Zhao, Xiaojuan Qi, Xiaoyong Shen, Jianping Shi, Jiaya Jia, details a

PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f

TensorFlow-ENet TensorFlow implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. This model was tested on th

segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN

FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo

Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a

DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute

SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a

Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm

Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur

Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne