Search Results for "forecasting" - Page 2
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Showing 73 open source projects for "forecasting"
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PyTorch Geometric Temporal
Spatiotemporal Signal Processing with Neural Machine Learning Models
...Moreover, it comes with an easy-to-use dataset loader, train-test splitter and temporal snaphot iterator for dynamic and temporal graphs. The framework naturally provides GPU support. It also comes with a number of benchmark datasets from the epidemiological forecasting, sharing economy, energy production and web traffic management domains. Finally, you can also create your own datasets. The package interfaces well with Pytorch Lightning which allows training on CPUs, single and multiple GPUs out-of-the-box. PyTorch Geometric Temporal makes implementing Dynamic and Temporal Graph Neural Networks quite easy - see the accompanying tutorial. ... -
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MiroThinker
MiroThinker is an open source deep research agent
...Rather than simply generating responses from a single prompt, the agent performs structured multi-step reasoning processes that involve searching for information, analyzing evidence, and synthesizing conclusions. The platform is optimized for research tasks such as financial forecasting, knowledge discovery, and large-scale information synthesis. MiroThinker has been evaluated on several agent benchmarks and has demonstrated strong performance on tests designed to measure deep research capabilities. -
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BoolFund
Funds have risks, and investments must be made cautiously.
A powerful fund analysis and management system software. It integrates multiple functions such as fund information, fund market data, fund analysis, fund management, and fund forecasting, maximizing the solution to problems investors face in choosing funds and managing returns. -
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Django-CRM - Free Open Source Software
Enterprise CRM software + Tasks management, Email marketing and more!
Django CRM system is easy to use and can be run on a personal laptop for a private entrepreneur (for example) or on a cloud web server for a large enterprise. Written in Python, CRM is an open-source software package for managing customer interactions and sales. This free CRM software is a powerful tool designed to optimize workflows, and support data-driven decisions. Key features include role-based access control, intuitive navigation, powerful filtering, and search functionalities. The... -
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Loss
The Brutalist Market Analyzer
LOSS is a high-speed, "split-stack" financial dashboard designed to strip away market noise. By combining mathematically rigorous technical indicators with VADER-powered AI sentiment analysis, LOSS delivers objective, real-time Buy, Sell, or Hold verdicts in under two seconds. Wrapped in a distraction-free, "Brutalist" user interface, this tool is built for traders who rely on data, not hype. Modern financial websites are bloated with ads, conflicting opinions, and unnecessary jargon.... -
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Premium Markets
Premium Markets is an automated financial technical analysis system.
Premium Markets is an automated financial technical analysis system. With Premium Markets you can edit and create your own indicators as a composition of more than a hundred common technical analysis functions. It implements a graphical environment for monitoring financial technical analysis of the main stocks and shares markets and currencies. The standalone application includes a full integration of ta-lib C/C++ libraries. Be aware that the provided App available for download may... -
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Transformers in Time Series
A professionally curated list of awesome resources
...The project was created to systematically organize the rapidly growing research field that applies transformer architectures to time series modeling tasks. It compiles literature from major conferences and journals and categorizes them by application domains such as forecasting, anomaly detection, and classification. The repository also provides a taxonomy that helps researchers understand different architectural variations of transformers designed for time series data. These models are particularly important because transformers can capture long-range dependencies in sequential data, which makes them well suited for complex temporal patterns in real-world datasets. -
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Zero to Mastery Deep Learning TensorFlow
All course materials for the Zero to Mastery Deep Learning with TF
...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. It also integrates milestone projects that simulate real-world scenarios, helping users translate abstract concepts into deployable solutions. -
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applied-ml
Papers & tech blogs by companies sharing their work on data science
The applied-ml repository is a rich, curated collection of papers, technical articles, and case-study blog posts about how machine learning (ML) and data-driven systems are applied in real production environments by major companies. Instead of focusing solely on theoretical ML research, this repo highlights industry-scale challenges: data collection, quality, infrastructure, feature stores, model serving, monitoring, scalability, and how ML is embedded in product workflows. It acts as a... -
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Capacity Planning & Management Software
Free & Open Capacity Planning Software in a Complete Virtual Machine
Every Profession has some sort of Resource to manage, be it materials, money, physical or logical resources & with it some vital queries to be answered: At what Rate is my Resource getting consumed? How Long will current stock last? What will be near future requirement? In Just Two Simple steps of Defining Your Resource & Actively Tracking its Consumption, you will be in total control of your Resource, with this Software. After starting this VM, from any PC on your Local Network,... -
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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
...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 to rapidly develop models for their specific time series needs, and benchmark them across multiple time series datasets. -
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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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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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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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WRF_ELEC
Storm electrification package for the WRF-ARW
NOTE: For WRF-ELEC with version 4.5.1, go to https://github.com/MicroTed/wrf4-elec This (older) project provides the external files need to compile electrification into the Weather Research and Forecasting (WRF) model (version 3.9.1.1 currently). It contains modules for the lightning discharge scheme, the screening layer parameterization, communications, and include code that calls these subroutines. Note that the required elliptic equation solver is a separate download from <http://sourceforge.net/projects/boxmg4wrf> -
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AlphaPy
Python AutoML for Trading Systems and Sports Betting
...Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow. Develop trading systems and analyze portfolios using MarketFlow and Quantopian's pyfolio. -
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ComplexEventExtraction
Expression pattern collection of Chinese compound event extraction
...It also discusses several event representations, including clauses, token sequences, and syntactic phrases. The project is intended as a research reference for event extraction, knowledge modeling, forecasting, and language-resource development. -
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fooltrader
Quant framework for stock
...Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and trading. Its applicable objects include quantitative traders, teachers, and students majoring in finance, people interested in economic data, programmers, and people who like freedom and the spirit of exploration. You could write the Strategy using an event-driven or time walkway and view and analyze the performance in a uniform way. -
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Fixer
A foreign exchange rates and currency conversion API
...One of its key strengths is its simplicity, as it uses straightforward RESTful endpoints and JSON responses that can be easily integrated into web or mobile applications. Fixer also supports time-series and fluctuation data, enabling more advanced financial analysis and forecasting use cases. While a free tier is available with some limitations, more advanced features such as higher request limits and additional base currencies are offered through paid plans. -
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bulbea
Deep Learning based Python Library for Stock Market Prediction
bulbea is an open-source Python library designed for financial analysis and stock market prediction using machine learning and deep learning techniques. The library provides tools for retrieving financial time series data, preprocessing market data, and training predictive models that estimate future price movements. bulbea integrates common machine learning frameworks such as TensorFlow and Keras to build neural network models capable of learning patterns in historical financial data. It... -
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Solar Wi-Fi weather station on ESP12
Solar Wi-Fi weather station on ESP12
#ESP.Meteo: Solar Wi-Fi weather station on ESP12 + ionistor + solar panel Current Functionality: *Forecasting the probability of frosts (according to the methods of Professor Brounov) *Forecast of the height of the lower edge of the cloud (VNGO by Selezneva) *Calculation of the height of the sensor according to the barometric formula (altimeter, for other projects) *Measurement of street temperature *Measurement of outdoor humidity *Measurement of street pressure *Calculation of the dew point *Monitoring of voltage on ionistors (charge-discharge control) *Monitoring the opening of the box flap with potatoes *Monitoring the system time-out every 5 minutes (operating time ~ 480 ms) *Monitoring the temperature on the balcony (the ability to connect up to 16 sensors DS18B20: 2 groups of 8 sensors per two APIKEY) *Sending data to the Thingspeak cloud *Sending data to Twitter -
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Personal Financier
Personal budgeting software with projections based on past trends.
Personal Financier is a tool to track expenses by category and then project the impact to the overall budget. Underspending in a given month increases the budget available to use in future months, and overspending reduces it. In this way, the budget adjusts over time to reflect actual spending. The easiest way to try it out is to use the demo account (password demo) that gets automatically setup on install. Enjoy! (See Wiki for more detailed information) -
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Cenobi
cost estimation and management accounting, using neural networks
Cenobi is designed for management accountants, not (only) for statisticians and data mining experts. Carefully arranged default settings make sure you can concentrate on Cenobi's many accounting features rather than worrying about setting up artificial neural networks or genetic algorithms, which are the main machine learning tools under Cenobi's hood. Cenobi's main benefits are: - ease of use - Utilizing artificial neural networks to estimate cost relationships, Cenobi is able to...
