Showing 35 open source projects for "forecasting"

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  • 1
    Auto-PyTorch

    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).
    Downloads: 0 This Week
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  • 2
    Padasip

    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.
    Downloads: 6 This Week
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  • 3
    Deep learning time series forecasting

    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. ...
    Downloads: 0 This Week
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  • 4
    Forecasting Best Practices

    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. ...
    Downloads: 0 This Week
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  • 5
    AlphaPy

    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.
    Downloads: 0 This Week
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  • 6
    fooltrader

    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.
    Downloads: 0 This Week
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  • 7

    Scadenzario

    A way to track your scheduled bills, recursive or not.

    It helps you tracking your scheduled bills or salary or whatever, recursive or not. In a nutshell, it helps to remember and analyze the budget.
    Downloads: 0 This Week
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  • 8
    bulbea

    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...
    Downloads: 0 This Week
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  • 9
    SnowMicroPyn

    SnowMicroPyn

    Python based reader for SnowMicroPen® .pnt measurements

    ...It is capable of measuring the bonding force between snow grains, with both high spatial resolution and high speed. The SMP can be used in different application areas as snow profiling (avalanche forecasting, snow stratigraphy, remote sensing ground truth), ski track characterization (ski racing) or snow runway characterization (stability testing).
    Downloads: 0 This Week
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  • 10
    Pragmatic CRM
    This software will be helpful in enhancing, retaining and acquiring new customer. Pragmatic CRM built within OpenERP is more robust than the existing CRM. Pragmatic CRM pragmatic customer relationship management
    Downloads: 0 This Week
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