Python Book-series Resources

Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC

This is the official repository of my book "Deep Learning with PyTorch Step-by-Step". Here you will find one Jupyter notebook for every chapter in the book.

USAD - UnSupervised Anomaly Detection on multivariate time series Scripts and utility programs for implementing the USAD architecture. Implementation

Time Series Research with Torch 这个开源项目主要是对经典的时间序列预测算法论文进行复现，模型主要参考自GluonTS，框架主要参考自Informer。 建立原因 相较于mxnet和TF，Torch框架中的神经网络层需要提前指定输入维度： # 建立线性层 TensorF

Dual Self-Attention Network for Multivariate Time Series Forecasting 20.10.26 Update: Due to the difficulty of installation and code maintenance cause

TS2Vec This repository contains the official implementation for the paper Learning Timestamp-Level Representations for Time Series with Hierarchical C

COWIN VACCINATION SLOT AUTO BOOKING (Bot with captcha solving & alerting capabilities. Never miss the vaccine slot.) June-10-2021/ 0030 hrs: 23 succes

A data preprocessing package for time series data. Design for machine learning and deep learning.

Soft DTW Loss Function for PyTorch in CUDA This is a Pytorch Implementation of Soft-DTW: a Differentiable Loss Function for Time-Series which is batch

pysesame3 Unofficial Python Library to communicate with SESAME 3 series products from CANDY HOUSE, Inc. This project aims to control SESAME 3 series d

tsflex is a toolkit for flexible time-series processing & feature extraction, making few assumptions about input data. Useful links Documentation Exam

A python library for easy manipulation and forecasting of time series.

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

Granger causality discovery for neural networks.

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Clairvoyance: A Pipeline Toolkit for Medical Time Series Authors: van der Schaar Lab This repository contains implementations of Clairvoyance: A Pipel

Repository for scripts and notebooks from the book: Programming PyTorch for Deep Learning

DOCTOSHOTGUN This script lets you automatically book a vaccine slot on Doctolib for today or tomorrow, following rules from the French Government. Pyt

TSForecasting This repository contains the implementations related to the experiments of a set of publicly available datasets that are used in the tim

neurodsp is a collection of approaches for applying digital signal processing to neural time series, including algorithms that have been proposed for the analysis of neural time series. It also includes simulation tools for generating plausible simulations of neural time series.

♞ pupalink A simple Python module to search and download books from SpringerLink. 🧪 This project is still in an early stage of development. Expect br

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

Python books free to read online or download

sankee Visualize changes in classified time series data with interactive Sankey plots in Google Earth Engine Contents Description Installation Using P

Stock Market Buy/Sell/Hold prediction Using convolutional Neural Network This repo is an attempt to implement the research paper titled "Algorithmic F

We are a group of like-minded people trying to make access to weather data in Python feel like a warm summer breeze, similar to other projects like rdwd for the R language, which originally drew our interest in this project.

Multidimensional LSTM BitCoin Time Series Using multidimensional LSTM neural networks to create a forecast for Bitcoin price. For notes around this co

Modeling High-Frequency Limit Order Book Dynamics Using Machine Learning Framework to capture the dynamics of high-frequency limit order books. Overvi

Advances in Financial Machine Learning Exercises Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by

...Minimizing the mean square error on future experience. - Richard S. Sutton BTGym Scalable event-driven RL-friendly backtesting library. Build on

geextract Google Earth Engine data extraction tool. Quickly obtain Landsat multispectral time-series for exploratory analysis and algorithm testing On

thunder scalable analysis of image and time series analysis in python Thunder is an ecosystem of tools for the analysis of image and time series data

Yet Another Timeseries Model (YATSM) master v0.6.x-maintenance Build Coverage Docs DOI | About Yet Another Timeseries Model (YATSM) is a Python packag

An open-source library of algorithms to analyse time series in GPU and CPU.

Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D

Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting This repository is the official implementation of Spectral Temporal Gr

FilterPy - Kalman filters and other optimal and non-optimal estimation filters in Python. NOTE: Imminent drop of support of Python 2.7, 3.4. See secti

PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W

Automated Time Series Models in Python (AtsPy) SSRN Report Easily develop state of the art time series models to forecast univariate data series. Simp

Anomaly Detection Toolkit (ADTK) Anomaly Detection Toolkit (ADTK) is a Python package for unsupervised / rule-based time series anomaly detection. As

Auto_TS: Auto_TimeSeries Automatically build multiple Time Series models using a Single Line of Code. Now updated with Dask. Auto_timeseries is a comp

matrixprofile-ts matrixprofile-ts is a Python 2 and 3 library for evaluating time series data using the Matrix Profile algorithms developed by the Keo

seglearn Seglearn is a python package for machine learning time series or sequences. It provides an integrated pipeline for segmentation, feature extr

Our article on Towards Data Science introduces the package and provides background information. Pytorch Forecasting aims to ease state-of-the-art time

pyts: a Python package for time series classification pyts is a Python package for time series classification. It aims to make time series classificat

STUMPY STUMPY is a powerful and scalable library that efficiently computes something called the matrix profile, which can be used for a variety of tim

Time Series Made Easy in Python darts is a python library for easy manipulation and forecasting of time series. It contains a variety of models, from

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

pmdarima Pmdarima (originally pyramid-arima, for the anagram of 'py' + 'arima') is a statistical library designed to fill the void in Python's time se

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

tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis

arch Autoregressive Conditional Heteroskedasticity (ARCH) and other tools for financial econometrics, written in Python (with Cython and/or Numba used

Technical Analysis Library in Python It is a Technical Analysis library useful to do feature engineering from financial time series datasets (Open, Cl

cosc428-structor I had an open-ended Computer Vision assignment to complete, and an out-of-copyright book that I wanted to turn into an ebook. Convent

ScanTailor Advanced The ScanTailor version that merges the features of the ScanTailor Featured and ScanTailor Enhanced versions, brings new ones and f

AntroPy is a Python 3 package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to e

tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis

swifter A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner. Blog posts Release 1.0.0 Fir

Arctic TimeSeries and Tick store Arctic is a high performance datastore for numeric data. It supports Pandas, numpy arrays and pickled objects out-of-

Time series analysis today is an important cornerstone of quantitative science in many disciplines, including natural and life sciences as well as eco

PyFlux PyFlux is an open source time series library for Python. The library has a good array of modern time series models, as well as a flexible array

Prophet: Automatic Forecasting Procedure Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends ar

tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti

Write Better Python Code This repository contains the code examples used in my Write Better Python Code series published on YouTube: https:/

MOSAIC: A modular single-molecule analysis interface MOSAIC is a single molecule analysis toolbox that automatically decodes multi-state nanopore data

Automatic Video Library Manager for TV Shows. It watches for new episodes of your favorite shows, and when they are posted it does its magic. Exclusiv

Open Library Open Library is an open, editable library catalog, building towards a web page for every book ever published. Are you looking to get star

PI Zero W Audio Book Motivation and requirements My dad is practically blind and at 80 years has trouble hearing and operating tiny or more complicate

Mylar Note that feature development has stopped as we have moved to Mylar3. EOL for this project is the end of 2020 and will no longer be supported. T

ForecastGA is a tool that combines a couple of popular libraries, Atspy and googleanalytics, with a few enhancements.

"To deal with hyper-planes in a 14 dimensional space, visualize a 3D space and say 'fourteen' very loudly. Everyone does it." - Geoff Hinton Overview

text recognition toolbox 1. 项目介绍 该项目是基于pytorch深度学习框架，以统一的改写方式实现了以下6篇经典的文字识别论文，论文的详情如下。该项目会持续进行更新，欢迎大家提出问题以及对代码进行贡献。 模型 论文标题 发表年份 模型方法划分 CRNN 《An End-t

MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

Non-AR Spatial-Temporal Transformer Introduction Implementation of the paper NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series For

"To deal with hyper-planes in a 14 dimensional space, visualize a 3D space and say 'fourteen' very loudly. Everyone does it." - Geoff Hinton Overview

Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin

Neural Networks from Scratch (NNFS) book code Code from the NNFS book (https://nnfs.io) separated by chapter.

SLM Lab Modular Deep Reinforcement Learning framework in PyTorch. Documentation: https://slm-lab.gitbook.io/slm-lab/ BeamRider Breakout KungFuMaster M

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

Code samples for "Neural Networks and Deep Learning" This repository contains code samples for my book on "Neural Networks and Deep Learning". The cod

imutils A series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displ