Search Results for "forecast"
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Showing 129 open source projects for "forecast"
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1
forecast
Forecasting Functions for Time Series and Linear Models
...Exponential smoothing state space models (ETS) including seasonal components. Residual checks, model accuracy, plots, forecast error measures etc. -
2
Prophet
Tool for producing high quality forecasts for time series data
...We’ve found it to perform better than any other approach in the majority of cases. We fit models in Stan so that you get forecasts in just a few seconds. Get a reasonable forecast on messy data with no manual effort. Prophet is robust to outliers, missing data, and dramatic changes in your time series. -
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Breezy Weather
A Material Design Weather Application
Breezy Weather is a privacy-focused, open-source Android weather app with a clean and modern interface. It aggregates weather data from various providers while respecting user privacy, offering features like current conditions, forecasts, and weather widgets. The app is designed to be lightweight, customizable, and completely ad-free. -
4
Graphical Forecast Editor
View and edit grids of meteorological values
Allows viewing and editing of weather data from weather models as two dimensional grids. Python scripting support hooks in the ingest, editing and product creation subsystems allow for customization. All network communication made through HTTP services. Enhanced version of the system used by national weather services. -
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MiroFish
A Simple and Universal Swarm Intelligence Engine
MiroFish is a next-generation artificial intelligence prediction engine that leverages multi-agent technology and swarm-intelligence simulation to model, simulate, and forecast complex real-world scenarios. The system extracts “seed” information from sources such as breaking news, policy documents, and market signals to construct a high-fidelity digital parallel world populated by thousands of virtual agents with independent memory and behavior rules. Users can inject variables or conditions into this simulated environment from a “god’s eye view,” enabling iterative prediction of future trends under different assumptions, which can be useful for decision support, scenario planning, or creative exploration. ... -
6
AI Hedge Fund
An AI Hedge Fund Team
...It integrates financial data collection, preprocessing, feature engineering, and predictive modeling to simulate decision-making in trading. The code shows workflows for pulling stock or market data, applying machine learning algorithms to forecast trends, and generating buy/sell/hold signals based on the predictions. Its structure is educational: intended more as a proof-of-concept than a ready-to-use financial product, giving learners insight into the mechanics of quantitative finance automation. The project underlines AI’s potential in investment strategies but also carries disclaimers that it is for research and not financial advice. ... -
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wttr.in
The right way to check the weather
wttr.in is a console-oriented weather forecast service that supports various information representation methods like terminal-oriented ANSI-sequences for console HTTP clients (curl, httpie, or wget), HTML for web browsers, or PNG for graphical viewers. Originally started as a small project, a wrapper for wego, intended to demonstrate the power of the console-oriented services, wttr.in became a popular weather reporting service, handling tens of millions of queries daily. -
8
PowerTrader_AI
Fully automated crypto trading powered by a custom price prediction AI
PowerTrader_AI is a fully open-source, automated cryptocurrency trading bot that combines a custom price prediction AI with a structured and tiered dollar-cost averaging (DCA) strategy to make real trading decisions on behalf of users. It continuously analyzes market data to forecast high and low price levels across multiple timeframes, using those predictions to determine when to open, scale into, or close positions automatically, which aims to take emotion out of trading and enforce discipline. The bot integrates with popular exchange APIs so it can execute real buy and sell orders, manage risk, and maintain position sizing without manual intervention, making it suitable for algorithmic traders who want hands-off operations. ... -
9
wego
Weather app for the terminal
wego is a weather client for the terminal. Config file for default location which can be overridden by commandline. Automatic config management with ingo. A working Go 1.5 environment (You can use goenv if your distribution does not support Go 1.5 yet). utf-8 terminal with 256 colors. A sane monospaced font containing all the required runes (I use dejavu sans mono). An API key for the backend. You can create an account and get a free API key by signing up. You can set the $WEGORC environment... -
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10
Anthropic SDK Python
Provides convenient access to the Anthropic REST API from any Python 3
The anthropic-sdk-python repository is the official Python client library for interacting with the Anthropic (Claude) REST API. It is designed to provide a user-friendly, type-safe, and asynchronous/synchronous capable interface for making chat/completion requests to models like Claude. The library includes definitions for all request and response parameters using Python typed objects, automatically handles serialization and deserialization, and wraps HTTP logic (timeouts, retries, error... -
11
ta4j
A Java library for technical analysis
...The wiki is the best place to start learning about ta4j. For more detailed questions, please use the issues tracker. We can calculate indicators over this bar series, in order to forecast the direction of prices through the study of past market data. Then we have to build our trading strategy. It is made of two trading rules, one for entry, the other for exit. Ta4j comes with a set of basic trading rules/strategies which can be combined using boolean operators. Trading strategies can be easily compared according to a set of analysis criteria. ... -
12
qryn
All-in-one Polyglot Observability stack with ClickHouse storage
...Make sure you have sufficient memory and disk resources allocated for your node service and clickhouse server when dealing with large amounts of data and fingerprints. We suggest 8GB RAM or higher for most setups with 100k-1M fingerprints. Observe your daily and weekly data consumption to forecast your disk usage requirements. Compression codecs and other optimizations can be performed at the ClickHouse level. -
13
NVIDIA Earth2Studio
Open-source deep-learning framework
...It provides a unified API that lets researchers, data scientists, and engineers build complex forecasting and analysis pipelines by combining modular prognostic and diagnostic AI models with a diverse range of real-world data sources such as global forecast systems, reanalysis datasets, and satellite feeds. The toolkit makes it easy to run deterministic and ensemble forecasts, swap models interchangeably, and process large geophysical datasets with Xarray structures, enabling experimentation with state-of-the-art deep learning models for climate and atmospheric prediction. Users can extend Earth2Studio with optional model packs, advanced data interfaces, statistical operators, and backend integrations that support flexible workflows from simple tests to large-scale operational inference. -
14
Cloud Cost Handbook
Set of guides meant to help explain often-times complex pricing
...It’s intended as an educational resource for developers, finance teams, and FinOps practitioners who need to understand how cloud costs are structured, what drives pricing across services, and how to estimate, optimize, and forecast spend without wading through dense official documentation. The handbook covers core concepts, pricing examples, cost-optimization techniques, and billing models across providers such as AWS, Azure, and GCP, with each section curated to improve clarity and accessibility for readers without deep financial or cloud billing expertise. ... -
15
StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery... -
16
Surya
Implementation of the Surya Foundation Model for Heliophysics
...Named after the Sanskrit word for “sun,” Surya is trained on nine years of high‑resolution solar imagery from NASA’s Solar Dynamics Observatory (SDO). It is designed to forecast solar phenomena—such as flares, solar wind, irradiance, and active region behavior—by predicting future solar images with a sophisticated long–short vision transformer architecture, thereby enabling improved space weather forecasting. Foresees solar flares, wind, EUV spectra, and active region formation in advance. Achieves approximately 16% improvement in forecasting accuracy over traditional methods. 366-million‑parameter foundation model capturing general-purpose solar representations. -
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GluonTS
Probabilistic time series modeling in Python
GluonTS is a Python package for probabilistic time series modeling, focusing on deep learning based models. GluonTS requires Python 3.6 or newer, and the easiest way to install it is via pip. We train a DeepAR-model and make predictions using the simple "airpassengers" dataset. The dataset consists of a single time-series, containing monthly international passengers between the years 1949 and 1960, a total of 144 values (12 years * 12 months). We split the dataset into train and test parts,... -
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NeuralProphet
A simple forecasting package
...We appreciate any help to improve and update the docs. Lagged regressors (measured features, e.g temperature sensor). Future regressors (in advance known features, e.g. temperature forecast). Country holidays & recurring special events. Sparsity of coefficients through regularization. Plotting for forecast components, model coefficients as well as final predictions. Automatic selection of training-related hyperparameters. -
19
HamInfo
The program provides various information of interest to radio amateurs
The program provides various information of interest to radio amateurs: - solar and magnetic dates - propagation forecasts on HF and VHF - DX cluster spots and their display on a map - list of contests for the coming week - tropo propagation forecast - auroral propagation forecast - meteor shower calendar - WAZ zone map - list of callsign prefixes assigned to countries -
20
python-client
GribStream.com python client for the historical weather forecasts API
The Python Client for https://GribStream.com is a robust library designed to interface seamlessly with GribStream, enabling efficient access to diverse meteorological datasets. This client facilitates leveraging datasets such as The National Blend of Models (NBM), The Global Forecast System (GFS), and The Rapid Refresh (RAP). GFS and RAP datasets are particularly well-suited for generating SkewT LogP charts. -
21
BRAMS-FURNAS
Weather Forescast Model with chemistry, aerosols and transport .
BRAMS IS A NUMERICAL MODELING SYSTEM DESIGNED FOR REGIONAL SCALE ATMOSPHERIC FORECASTING AND RESEARCH, WITH FOCUS ON ATMOSPHERIC CHEMISTRY, AIR QUALITY AND BIOGEOCHEMICAL CYCLES. -
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Weather Cast
A desktop weather app powered by AI
Weather app is a desktop weather app for Windows OS that shows detailed weather information for the searched city. The dashboard shows the current temperature of the city, description of temperature, pressure, wind, humidity, dew point, uv index, local time, air pollution index. -
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Premium Markets
Premium Markets is an automated financial technical analysis system.
...Full installation instructions can be found at http://www.premiummarkets.uk/html/swtui.html#Download . I would also like to bring to your attention that, in its advanced version, Premium Markets also provides a Forecast machine learning engine based on neural networks. See http://www.premiummarkets.uk/ for documentation and a workable demo of the trend forecast and prediction engine. -
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HomeBank
Free, easy, personal accounting for everyone
«HomeBank» is the software you have always wanted to manage your personal accounts. It brings you many features to analyze your finances in a detailed way instantly and dynamically with powerfull report tools based on filtering and graphical charts. -
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Based on Debian Stable Installation tool: Calamares Besgnulinux is for both new and weak machines and end users (newbies). Besgnulinux tries to be fast, lightweight, easy to use and stable. It is designed to meet every need with window manager sessions like JWM, Openbox. Instead of background elements, the system is under user control. It does the same things that high-resource desktops like KDE and Gnome do. But it does the job with very little resources. Besgnulinux's goal is to...
