Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Aialpha | 1,766 | 5 years ago | 8 | mit | Python | |||||
Use unsupervised and supervised learning to predict stocks | ||||||||||
Deep_learning_machine_learning_stock | 1,353 | a year ago | 4 | mit | Jupyter Notebook | |||||
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders. | ||||||||||
Stockpriceprediction | 1,132 | 2 years ago | 10 | mit | Jupyter Notebook | |||||
Stock Price Prediction using Machine Learning Techniques | ||||||||||
Deepdow | 790 | a year ago | 5 | February 16, 2021 | 26 | apache-2.0 | Python | |||
Portfolio optimization with deep learning. | ||||||||||
Introneuralnetworks | 735 | 6 years ago | 5 | mit | Python | |||||
Introducing neural networks to predict stock prices | ||||||||||
Pixiu | 309 | a year ago | 4 | mit | Python | |||||
This repository introduces PIXIU, an open-source resource featuring the first financial large language models (LLMs), instruction tuning data, and evaluation benchmarks to holistically assess financial LLMs. Our goal is to continually push forward the open-source development of financial artificial intelligence (AI). | ||||||||||
Astock | 142 | 2 years ago | 6 | Jupyter Notebook | ||||||
Astock | ||||||||||
Relataly Public Python Tutorials | 109 | 2 years ago | 2 | cc-by-sa-4.0 | Jupyter Notebook | |||||
Beginner-friendly collection of Python notebooks for various use cases of machine learning, deep learning, and analytics. For each notebook there is a separate tutorial on the relataly.com blog. | ||||||||||
Stocker | 108 | 2 years ago | 13 | November 03, 2021 | 14 | mit | Jupyter Notebook | |||
Stock Price Prediction | ||||||||||
Sci Pype | 96 | 5 years ago | 3 | apache-2.0 | Python | |||||
A Machine Learning API with native redis caching and export + import using S3. Analyze entire datasets using an API for building, training, testing, analyzing, extracting, importing, and archiving. This repository can run from a docker container or from the repository. |