Search Results for "delphi artificial intelligence"
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Showing 12 open source projects for "delphi artificial intelligence"
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FinGPT
Open-Source Financial Large Language Models
FinGPT is an open-source, finance-specialized large language model framework that blends the capabilities of general LLMs with real-time financial data feeds, domain-specific knowledge bases, and task-oriented agents to support market analysis, research automation, and decision support. It extends traditional GPT-style models by connecting them to live or historical financial datasets, news APIs, and economic indicators so that outputs are grounded in relevant and recent market conditions... -
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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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NeuralProphet
A simple forecasting package
NeuralProphet bridges the gap between traditional time-series models and deep learning methods. It's based on PyTorch and can be installed using pip. A Neural Network based Time-Series model, inspired by Facebook Prophet and AR-Net, built on PyTorch. You can find the datasets used in the tutorials, including data preprocessing examples, in our neuralprophet-data repository. The documentation page may not we entirely up to date. Docstrings should be reliable, please refer to those when in... -
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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... -
Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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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. -
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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... -
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AnyTrading
The most simple, flexible, and comprehensive OpenAI Gym trading
gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex. -
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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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Turn your scanner into a free document reader for invoices (e.g. for e-banking) with the help of tesseract-ocr available for many unix (and also windows) platforms.
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Open Exchange (OpEx)
The open source Algorithmic Trading System
OpEx is an application suite that includes the main building blocks of commercial electronic trading systems. All OpEx applications run on distributed system architectures. -
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The purpose of this program is to prove that given a finite number of Monkeys and a finite amount of time one monkey will be able to make more money off the stock market than any human being. Checkout our web site for an uncorrupted download.
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