Search Results for "python feature selection"
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Showing 9 open source projects for "python feature selection"
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AI Hedge Fund
An AI Hedge Fund Team
This repository demonstrates how to build a simplified, automated hedge fund strategy powered by AI/ML. 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... -
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FinRobot
An Open-Source AI Agent Platform for Financial Analysis using LLMs
FinRobot is an open-source AI framework focused on automating financial data workflows by combining data ingestion, feature engineering, model training, and automated decision-making pipelines tailored for quantitative finance applications. 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... -
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Apache OpenOffice
The free and Open Source productivity suite
Free alternative for Office productivity tools: Apache OpenOffice - formerly known as OpenOffice.org - is an open-source office productivity software suite containing word processor, spreadsheet, presentation, graphics, formula editor, and database management applications. OpenOffice is available in many languages, works on all common computers, stores data in ODF - the international open standard format - and is able to read and write files in other formats, included the format used by the... -
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AutoTrader
A Python-based development platform for automated trading systems
AutoTrader is a Python-based platform—now archived—designed to facilitate the full lifecycle of automated trading systems. It provides tools for backtesting, strategy optimization, visualization, and live trading integration. A feature-rich trading simulator, supporting backtesting and paper trading. The 'virtual broker' allows you to test your strategies in a risk-free, simulated environment before going live. -
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TradingGym
Trading backtesting environment for training reinforcement learning
...Licensed under MIT. This training environment was originally designed for tickdata, but also supports OHLC data format. WIP. The list contains the feature columns to use in the trading status. -
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TradeMaster
TradeMaster is an open-source platform for quantitative trading
TradeMaster is a first-of-its-kind, best-in-class open-source platform for quantitative trading (QT) empowered by reinforcement learning (RL), which covers the full pipeline for the design, implementation, evaluation and deployment of RL-based algorithms. TradeMaster is composed of 6 key modules: 1) multi-modality market data of different financial assets at multiple granularities; 2) whole data preprocessing pipeline; 3) a series of high-fidelity data-driven market simulators for mainstream... -
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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... -
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If you are long term Investors, you use Linux operating system and love command line utilities then STOCKY is for you. As a key feature, stocky will tell you whether to hold or sell your stocks based on stoploss you have set.
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A collection of portfolio management components. Sharpe Model for selection of an initial portfolio is already implemented. A genetic algorithms package, also written in java, is used for the search of the best portfolio variants.
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Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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