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Python AutoML for Trading Systems and Sports Betting
The main features of scottfreellc/alphapy are: Algorithmic Trading Tools, Automated Machine Learning, Trading and Backtesting.
Open-source alternatives to scottfreellc/alphapy include: karpathy/autoresearch — Autoresearch is an autonomous machine learning research agent and architecture search framework. It employs a… autogluon/autogluon — AutoGluon is an automated machine learning framework and multimodal library designed to automate the end-to-end… ludwig-ai/ludwig — Ludwig is a multimodal machine learning platform and low-code framework designed for building, training, and deploying… charliedream1/ai_quant_trade — ai_quant_trade is an AI-driven quantitative trading platform that enables the development, backtesting, and deployment… bayesian-optimization/bayesianoptimization — This is a Bayesian optimization library for Python designed to find the maximum value of expensive black box… microsoft/ai-edu — ai-edu is a comprehensive AI education curriculum and machine learning courseware collection. It provides theoretical…
Autoresearch is an autonomous machine learning research agent and architecture search framework. It employs a closed-loop system to programmatically rewrite training and architecture source code to discover optimal language model configurations. The system iteratively modifies code and evaluates performance metrics to improve model quality based on a target objective. It optimizes model performance and training efficiency by tracking validation bits per byte, which allows for a fair comparison of architectural changes independently of vocabulary size. The framework manages the full training
AutoGluon is an automated machine learning framework and multimodal library designed to automate the end-to-end pipeline from data preprocessing to high-accuracy model training and validation. It functions as an automated model trainer for tabular, image, text, and time series data, as well as a tool for time series forecasting and foundation model finetuning. The project is distinguished by its ability to jointly process and fuse different data types, allowing for the construction of multimodal neural networks that integrate images, text, and structured tables. It supports zero-shot inferenc
aiquanttrade is an AI-driven quantitative trading platform that enables the development, backtesting, and deployment of trading strategies powered by machine learning and artificial intelligence. It provides a complete local environment for quantitative research, simulation, and automated live trading through brokerage APIs, supporting both historical backtesting and real-time paper trading without capital risk. The platform distinguishes itself through a modular, event-driven architecture that separates strategy logic from execution, allowing rule-based and machine learning models to be co
Ludwig is a multimodal machine learning platform and low-code framework designed for building, training, and deploying neural networks. It enables the construction of models that process text, images, audio, and tabular data through a unified interface using declarative configuration files rather than custom code. The system features a specialized low-code framework for large language models, supporting supervised fine-tuning, preference alignment, and a constrained decoding tool to force structured data output via logit extraction. It also includes an automated model architecture search to i