Showing 14 open source projects for "spreadsheet machine learning"

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  • 1
    AIQuant

    AIQuant

    AI-powered platform for quantitative trading

    ...Stock trading strategies: large models, factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph networks, high-frequency trading, etc. Resource summary: network-wide resource summary, practical cases, paper interpretation, and code implementation.
    Downloads: 1 This Week
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  • 2
    PyBroker

    PyBroker

    Algorithmic Trading in Python with Machine Learning

    Are you looking to enhance your trading strategies with the power of Python and machine learning? Then you need to check out PyBroker! This Python framework is designed for developing algorithmic trading strategies, with a focus on strategies that use machine learning. With PyBroker, you can easily create and fine-tune trading rules, build powerful models, and gain valuable insights into your strategy’s performance.
    Downloads: 0 This Week
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  • 3
    Qlib

    Qlib

    Qlib is an AI-oriented quantitative investment platform

    Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. With Qlib, users can easily try their ideas to create better Quant investment strategies. At the module level, Qlib is a platform that consists of...
    Downloads: 0 This Week
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  • 4
    FinMind

    FinMind

    Open Data, more than 50 financial data

    ...Regardless of the program, you can download data through the api provided by FinMind, or you can download data directly from the website. After data is available, statistical analysis, regression analysis, time series analysis, machine learning, and deep learning can be performed. For individual stocks, provide visual analysis of technical, fundamental, and chip levels. According to different strategies, back-test analysis is performed to provide performance, profit and loss, and stock selection targets of different strategy investment portfolios.
    Downloads: 1 This Week
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  • 5
    PyTorch Forecasting

    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 with...
    Downloads: 2 This Week
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  • 6
    AI Hedge Fund

    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. ...
    Downloads: 0 This Week
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  • 7
    FinRobot

    FinRobot

    An Open-Source AI Agent Platform for Financial Analysis using LLMs

    ...It provides developers and quants with structured modules to fetch market data, process time series, generate technical indicators, and construct features appropriate for machine learning models, while also supporting backtesting and evaluation metrics to measure strategy performance. Built with modularity in mind, FinRobot allows users to plug in custom models — from classical algorithms to deep learning architectures — and orchestrate components in pipelines that can run reproducibly across experiments. ...
    Downloads: 0 This Week
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  • 8
    Premium Markets

    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.
    Downloads: 3 This Week
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  • 9

    Kalshi-Quant-TeleBot

    Kalshi Advanced Quantitative Trading Bot is an enterprise-grade

    ...Built with cutting-edge quantitative algorithms and professional risk management, it provides institutional-quality trading capabilities with user-friendly control The Kalshi Advanced Quantitative Trading Bot is a professional-grade automated trading system designed specifically for event-based markets on the Kalshi platform. This bot leverages advanced quantitative strategies, machine learning techniques, and real-time data analysis to identify profitable trading opportunities while maintaining robust risk management protocols. Built with a modular architecture, the system combines Python-based trading algorithms with a JavaScript Telegram bot interface for dynamic monitoring and interaction. The bot is designed to operate continuously, making data-driven decisions based on news sentiment analysis, statistical arbitrage opportunities
    Downloads: 0 This Week
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  • 10
    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...
    Downloads: 0 This Week
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  • 11
    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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  • 12
    A.I. Stock Trends With WEKA & TA-Lib

    A.I. Stock Trends With WEKA & TA-Lib

    A Repository Of The Java Programs Presented in the Videos.

    This is the open/public source code repository for the Java programs shown in the YouTube videos - A.I. Stock Trends With WEKA, TA-Lib and more https://www.youtube.com/channel/UCPxmgFZDS7F06UBBxH5b4mg
    Downloads: 0 This Week
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  • 13
    Cenobi

    Cenobi

    cost estimation and management accounting, using neural networks

    ...Although Cenobi is particularly suitable for management accounting purposes, it can also be used as a general machine learning tool. The neural networks at the heart of the program are fully object-oriented and therefore highly adaptable. You are very welcome to use them under the GPLv3.
    Downloads: 0 This Week
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  • 14
    R-Portfolio
    R-Portfolio - breakeven optimally diversified investment portfolio. Оптимально диверсифицированный инвестиционный портфель.
    Downloads: 0 This Week
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