Search Results for "time series forecasting"
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Showing 386 open source projects for "time series forecasting"
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PyTorch Forecasting
Time series forecasting with PyTorch
PyTorch Forecasting aims to ease state-of-the-art time series forecasting with neural networks for both real-world cases and research alike. The goal is to provide a high-level API with maximum flexibility for professionals and reasonable defaults for beginners. A time series dataset class that abstracts handling variable transformations, missing values, randomized subsampling, multiple history lengths, etc. A base model class that provides basic training of time series models along... -
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Chronos Forecasting
Pretrained (Language) Models for Probabilistic Time Series Forecasting
Chronos is a family of pretrained time series forecasting models based on language model architectures. A time series is transformed into a sequence of tokens via scaling and quantization, and a language model is trained on these tokens using the cross-entropy loss. Once trained, probabilistic forecasts are obtained by sampling multiple future trajectories given the historical context. Chronos models have been trained on a large corpus of publicly available time series data, as well... -
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Deep learning time series forecasting
Deep learning PyTorch library for time series forecasting
Example image Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state-of-the-art models (transformers, attention models, GRUs) and cutting-edge concepts with easy-to-understand interpretability metrics, cloud provider integration, and model serving capabilities. Flow Forecast was the first time series framework to feature support for transformer-based models and remains the only true end-to-end deep learning for time series... -
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sktime
A unified framework for machine learning with time series
sktime is a library for time series analysis in Python. It provides a unified interface for multiple time series learning tasks. Currently, this includes time series classification, regression, clustering, annotation, and forecasting. It comes with time series algorithms and scikit-learn compatible tools to build, tune and validate time series models. Our objective is to enhance the interoperability and usability of the time series analysis ecosystem in its entirety. sktime provides a unified... -
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Darts
A python library for easy manipulation and forecasting of time series
darts is a Python library for easy manipulation and forecasting of time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn. The library also makes it easy to backtest models, combine the predictions of several models, and take external data into account. Darts supports both univariate and multivariate time series and models. The ML-based models can... -
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pandas
Fast, flexible and powerful Python data analysis toolkit
pandas is a Python data analysis library that provides high-performance, user friendly data structures and data analysis tools for the Python programming language. It enables you to carry out entire data analysis workflows in Python without having to switch to a more domain specific language. With pandas, performance, productivity and collaboration in doing data analysis in Python can significantly increase. pandas is continuously being developed to be a fundamental high-level building... -
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Prophet
Tool for producing high quality forecasts for time series data
Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Prophet is used in many applications across Facebook for producing reliable forecasts for planning and goal setting... -
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Nixtla
Fast forecasting with statistical and econometric models
StatsForecast offers a collection of widely used univariate time series forecasting models, including automatic ARIMA, ETS, CES, and Theta modeling optimized for high performance using numba. It also includes a large battery of benchmarking models. Lightning-fast forecasting with statistical and econometric models. -
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InfluxDB
The open source time series database
InfluxDB is an open source time series datastore designed to handle high write and query loads. Time series is currently the fastest growing database category there is, and InfluxDB is here to ensure businesses can keep up. InfluxDB provides infrastructure and application monitoring, IoT monitoring and analytics and more. It has APIs for storing and querying data, processing it in the background for ETL or monitoring and alerting purposes. This data can also be visualized, explored and more... -
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Merlion
A Machine Learning Framework for Time Series Intelligence
Merlion is a Python library for time series intelligence. It provides an end-to-end machine learning framework that includes loading and transforming data, building and training models, post-processing model outputs, and evaluating model performance. It supports various time series learning tasks, including forecasting, anomaly detection, and change point detection for both univariate and multivariate time series. This library aims to provide engineers and researchers a one-stop solution... -
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TimescaleDB
An open-source time-series SQL database optimized for fast ingest
TimescaleDB is the open-source relational database for time-series and analytics. Build powerful data-intensive applications. Become instantly productive with full SQL. Rely on the same PostgreSQL you know, love, and trust. Hyperfunctions make time series easier. Achieve 10-100x faster queries than with vanilla PostgreSQL, InfluxDB, MongoDB. Write millions of data points per second per node. Horizontally scale to petabytes. Don’t worry about cardinality. Simplify your stack, ask more complex... -
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Multi Theft Auto: San Andreas
Multi Theft Auto is a game engine
Multi Theft Auto (MTA) is a software project that adds network play functionality to Rockstar North's Grand Theft Auto game series, in which this functionality is not originally found. It is a unique modification that incorporates an extendable network play element into a proprietary commercial single-player PC game. Multi Theft Auto is based on code injection and hooking techniques whereby the game is manipulated without altering any original files supplied with the game. The software... -
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Prometheus
Open source monitoring system and time series database
Prometheus is a leading open source systems and service monitoring solution. It works by collecting metrics from configured targets at given intervals, evaluating rule expressions, and then displaying the results. It can also signal an alert if a condition is observed to be true. What sets Prometheus apart from other monitoring systems is its highly dimensional data model, powerful query language, autonomous single server nodes, among many other distinguishing features. It also offers... -
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PlotJuggler
The Time Series Visualization Tool that you deserve
Fast, intuitive, and extensible time series visualization tool. Its Drag & Drop interface is designed to maximize both simplicity and speed. PlotJuggler is perfect for visualizing logs, offline and real-time data, and it can be used in multiple fields. PlotJuggler can be connected to an external application using any inter-process communication and display data in real time. Thanks to its plugin-based architecture, it is easy to add new data sources and functionalities. If needed, you can... -
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Label Studio
Label Studio is a multi-type data labeling and annotation tool
The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Detect objects on image, bboxes, polygons, circular, and keypoints supported. Partition image into multiple segments. Use ML models to pre-label and optimize the process. Label Studio is an open-source data labeling tool. It lets you label data types like audio, text, images, videos, and time series with a simple and straightforward UI and export to various model formats. It can... -
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Node exporter
Exporter for machine metrics
Power your metrics and alerting with a leading open-source monitoring solution. Prometheus implements a highly dimensional data model. Time series are identified by a metric name and a set of key-value pairs. PromQL allows slicing and dicing of collected time series data in order to generate ad-hoc graphs, tables, and alerts. Prometheus has multiple modes for visualizing data: a built-in expression browser, Grafana integration, and a console template language. Prometheus stores time series... -
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Nixtla ML
TimeGPT-1: production ready pre-trained Time Series Foundation Model
TimeGPT is a production ready, generative pretrained transformer for time series. It's capable of accurately predicting various domains such as retail, electricity, finance, and IoT with just a few lines of code. Whether you're a bank forecasting market trends or a startup predicting product demand, TimeGPT democratizes access to cutting-edge predictive insights, eliminating the need for a dedicated team of machine learning engineers. A generative model for time series. TimeGPT is capable... -
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Explorer
Series (one-dimensional) and dataframes (two-dimensional)
Explorer brings series (one-dimensional) and data frames (two-dimensional) to Elixir for fast data exploration. -
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Point Cloud Library
A standalone, large scale, open project for 2D/3D image processing
The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and thus free for commercial and research use. Whether you’ve just discovered PCL or you’re a long time veteran, this page contains links to a set of resources that will help consolidate your knowledge on PCL and 3D processing. An additional Wiki resource for developers is available too. To simplify both usage and development... -
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VictoriaMetrics
VictoriaMetrics: fast, cost-effective monitoring solution
VictoriaMetrics is a fast, cost-effective and scalable monitoring solution and time series database. VictoriaMetrics is available in binary releases, Docker images, Snap packages and source code. Just download the latest version of VictoriaMetrics. VictoriaMetrics is developed at a fast pace, so it is recommended periodically checking the CHANGELOG and performing regular upgrades. It can be used as long-term storage for Prometheus. See these docs for details. It can be used as a drop... -
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River ML
Online machine learning in Python
River is a Python library for online machine learning. It aims to be the most user-friendly library for doing machine learning on streaming data. River is the result of a merger between creme and scikit-multiflow. -
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hctsa
Highly comparative time-series analysis
hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix. -
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Stanford CoreNLP
Stanford CoreNLP, a Java suite of core NLP tools
CoreNLP is your one stop shop for natural language processing in Java! CoreNLP enables users to derive linguistic annotations for text, including token and sentence boundaries, parts of speech, named entities, numeric and time values, dependency and constituency parses, coreference, sentiment, quote attributions, and relations. CoreNLP currently supports 6 languages, Arabic, Chinese, English, French, German, and Spanish. The centerpiece of CoreNLP is the pipeline. Pipelines take in raw text... -
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Orion
A machine learning library for detecting anomalies in signals
Orion is a machine-learning library built for unsupervised time series anomaly detection. Such signals are generated by a wide variety of systems, few examples include telemetry data generated by satellites, signals from wind turbines, and even stock market price tickers. We built this to provide one place where users can find the latest and greatest in machine learning and deep learning world including our own innovations. Abstract away from the users the nitty-gritty about preprocessing... -
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tsai
Time series Timeseries Deep Learning Machine Learning Pytorch fastai
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series tasks like classification, regression, forecasting, and imputation. Starting with tsai 0.3.0 tsai will only install hard dependencies. Other soft dependencies (which are only required for selected tasks) will not be installed by default (this is the recommended approach. If you require any of the dependencies that is not installed, tsai will ask you to install...