Search Results for "time series forecasting java" - Page 2
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Showing 113 open source projects for "time series forecasting java"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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. -
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Prometheus JVM Client
Prometheus instrumentation library for JVM applications
It supports Java, Clojure, Scala, JRuby, and anything else that runs on the JVM. If you use Maven, you can simply reference the assets below. The latest version can be found on in the maven repository for io.prometheus. By default, counters, histograms, and summaries export an additional series suffixed with _created and a value of the unix timestamp for when the metric was created. Building the repository needs Java 11 (The project the project still supports Java 6 and Java versions > 11... -
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gulp
A toolkit to automate & enhance your workflow
gulp is a streaming build system that automates slow, repetitive and time-consuming tasks in your development workflow. It is simple and easy to use with only a minimal API surface, but powerful enough to compose efficient build pipelines. gulp is flexible and composable, and is also platform-agnostic, which means you can use it with PHP, .NET, Java and many other platforms. It’s got a strong ecosystem of npm modules and over 3000 curated, community-built plugins, so you can achieve... -
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NullAway
A tool to help eliminate NullPointerExceptions (NPEs) in your code
NullAway is a tool to help eliminate NullPointerExceptions (NPEs) in your Java code. To use NullAway, first add @Nullable annotations in your code wherever a field, method parameter, or return value may be null. Given these annotations, NullAway performs a series of type-based, local checks to ensure that any pointer that gets dereferenced in your code cannot be null. NullAway is similar to the type-based nullability checking in the Kotlin and Swift languages, and the Checker Framework and Eradicate null checkers for Java. ... -
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AngClust
AngClust: Angle-based feature clustering for time series
Citation: Aimin Li, Siqi Xiong, Junhuai Li, Saurav Mallik, Yajun Liu, Rong Fei, Hongfang Zhou, Guangming Liu. AngClust: Angle Feature-Based Clustering for Short Time Series Gene Expression Profiles. January 2022. IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM. DOI: 10.1109/TCBB.2022.3192306 Full text: https://ieeexplore.ieee.org/document/9833353/ https://pubmed.ncbi.nlm.nih.gov/35853049/ Highlights * We proposed a novel clustering algorithm based... -
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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in... -
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STOR2RRD
Storage, SAN, LAN Performance Monitoring: IBM,NetApp,Hitachi,HPE,EMC
The tool offers you end-to-end views of your storage environment including LAN and SAN and can save you significant money in operation monitoring and by predicting utilization bottlenecks in your virtualized environment. You can also generate policy-based alerts, view overall health status of your systems, reduce service downtime, use capacity and forecasting data - Real-time storage performance visibility in LAN and SAN multi-vendor environment - Historical reporting (graph,... -
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LakshmiDROP
Fixed Income Analytics, Portfolio Construction, Asset Backed Cost
DROP implements the model libraries and provides systems for fixed income valuation and adjustments, asset allocation and transaction cost analytics, and supporting libraries in numerical optimization and statistical learning. DROP is composed of four main libraries: [Asset Allocation] (https://lakshmidrip.github.io/DROP/AssetAllocationModule.html) [Fixed Income Analytics] (https://lakshmidrip.github.io/DROP/FixedIncomeModule.html) [Numerical Optimization]... -
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Zero to Mastery Deep Learning TensorFlow
All course materials for the Zero to Mastery Deep Learning with TF
This project is a comprehensive, code-first deep learning curriculum built around TensorFlow and Keras, designed to guide learners from foundational concepts to practical model deployment through hands-on experimentation. It is structured as a series of progressively complex Jupyter notebooks that emphasize writing and understanding code before diving into theory, reinforcing learning through repetition and application. The material covers core machine learning workflows including regression, classification, computer vision, natural language processing, and time series forecasting, allowing users to build a well-rounded understanding of modern AI tasks. ... -
AI-generated apps that pass security reviewRetool lets you generate dashboards, admin panels, and workflows directly on your data. Type something like “Build me a revenue dashboard on my Stripe data” and get a working app with security, permissions, and compliance built in from day one. Whether on our cloud or self-hosted, create the internal software your team needs without compromising enterprise standards or control.
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NKTgLaw
Core library & API for the NKTg Law (Nguyen Khanh Tung). Includes core
Core library & API for the NKTg Law (Nguyen Khanh Tung). Includes core implementation, REST/gRPC API, and 150+ client wrappers -
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eCxx
A C++ library for AVR and NodeMCU
NOTE: This project is marked with 'Status: Abandoned' on SourceForge because not enough time can be dedicated to this project. However it may still get sporadic commits to the repository. eCxx is a library for AVR and NodeMCU tailored for micro LED displays and lighting effects. eCxx is utilizing Makefile build system. Java and Python based applications/tools are also included to ease the development and debugging process using the host PC. -
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A tool to support individuals and teams using high-maturity, metrics-intensive project management methodologies [such as PSP(SM) and TSP(SM)]. Supports personal and team earned value tracking and forecasting; simplifies metrics collection and analysis.
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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. -
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Auto-PyTorch
Automatic architecture search and hyperparameter optimization
...To bring the best of these two worlds together, we developed Auto-PyTorch, which jointly and robustly optimizes the network architecture and the training hyperparameters to enable fully automated deep learning (AutoDL). Auto-PyTorch is mainly developed to support tabular data (classification, regression) and time series data (forecasting). The newest features in Auto-PyTorch for tabular data are described in the paper "Auto-PyTorch Tabular: Multi-Fidelity MetaLearning for Efficient and Robust AutoDL" (see below for bibtex ref). Details about Auto-PyTorch for multi-horizontal time series forecasting tasks can be found in the paper "Efficient Automated Deep Learning for Time Series Forecasting" (also see below for bibtex ref). -
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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 forecasting framework. ... -
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ImageJ2x
Java Image Processing Program
ImageJ2x is medical image processing program inspired by NIH Image for the Macintosh. It can display, edit, analyze, process, save and print 8-bit, 16-bit and 32-bit images. There can be many image formats including TIFF, GIF, JPEG, BMP, DICOM, PNG, FITS and "raw" and ... Read and supports "stacks" (stack), a series of images that share a single window. The program supports simultaneous that number of windows (images), limited only by available memory. It is multithreaded, so that... -
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Padasip
Python Adaptive Signal Processing
Padasip (Python Adaptive Signal Processing) is a Python library tailored for adaptive filtering and online learning applications, particularly in signal processing and time series forecasting. It includes a variety of adaptive filter algorithms such as LMS, RLS, and their variants, offering real-time adaptation to changing environments. The library is lightweight, well-documented, and ideal for research, prototyping, or teaching purposes. Padasip supports both supervised and unsupervised filtering modes and is built to be modular and extensible, making it easy to integrate into larger machine learning pipelines or control systems. -
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OpenTSDB
A scalable, distributed time series database
OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase. OpenTSDB was written to address a common need: store, index and serve metrics collected from computer systems (network gear, operating systems, applications) at a large scale, and make this data easily accessible and graphable. Store and serve massive amounts of time series data without losing granularity. Generate graphs from the GUI, pull from the HTTP API, choose an open source front-end. OpenTSDB... -
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KairosDB
Fast scalable time series database
KairosDB is a fast distributed scalable time series database written on top of Cassandra. -
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Heroic
The Heroic Time Series Database
Heroic is a scalable time-series database developed by Spotify, designed for real-time analytics and monitoring of large-scale systems. -
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TSMiner is a software program for reconstructing time-specific regulatory networks for time-series expression data. TSMiner has three key modules: first, predicting the time-specific activated/repressed transcription factors (TFs); second, predicting the biological pathways associated with the predicted TFs; third, merging the TFs and pathways into time-specific regulatory networks. TSMiner provides extensive interactive operations to help users explore the results of each module. For...
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
Time series forecasting is one of the most important topics in data science. Almost every business needs to predict the future in order to make better decisions and allocate resources more effectively. This repository provides examples and best practice guidelines for building forecasting solutions. The goal of this repository is to build a comprehensive set of tools and examples that leverage recent advances in forecasting algorithms to build solutions and operationalize them. ... -
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XAOP
A lghtweight AOP(Android) application framework
A lightweight AOP (Android) application framework, including the most practical AOP applications. It is better to act than to be excited, so hurry up and click on the user manual to experience it! In order to facilitate the quick integration of the X series framework library, I provide an empty shell template for your reference. Supports quick click slices @SingleClick, and supports setting the time interval of quick clicks. Supports dynamic application for permission slices @Permission, and... -
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SwaNN
PSO for neural networks
SwaNN is a basic framework for neural networks based on particle swarm optimization (using the Python package PySwarms (https://pyswarms.readthedocs.io/en/latest/). The zip file contains the main programs in SwaNN.py and around 30 examples : - classification - regression - time series forecasting I need some help for class building (I am not an expert in Python nor in OOP), if somebody is interested in it... In Google Colab : https://colab.research.google.com/drive/1u6SOydDUThUrhTfaic2NiyDhh1ZGRJsH?usp=sharing What's new: - the jupyter notebook is reorganized and clean -
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MTSF
Multivariate Time Series Forecasting.
This is the implementation of the technique allowing for Multivariate Time Series Forecasting using basic knowledge of Calculus and Algebra at the High School level.
