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machine-learning-for-trading 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅。
Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.
AlgoTraders / stock-analysis-engine
stock-analysis-engine
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
stock-analysis-engine 是用 Jupyter Notebook 编写的学习资料，用于系统学习与查阅。
目前累计 1.2k star、270 fork，主要语言为 Jupyter Notebook，项目始于 2018 年。最近状态：已有一段时间未更新。适合：想补齐某块知识的开发者。
中文介绍优先采用本站人工维护条目；无维护条目时依据 GitHub 公开字段（语言、主题、星标、提交时间）自动生成，未经项目方确认，不构成选型结论。AlgoTraders/stock-analysis-engine 是一个以 Jupyter Notebook 为主的开源项目，目前累计 1.2k star、270 fork，较长时间未更新。主要方向：algorithmic-trading、backtesting、深度学习、deep-learning-tutorial、deep-neural-networks、Docker。
依据 GitHub 公开字段（语言、主题、星标、提交时间）自动生成，未经人工逐项核实。algorithmic-tradingbacktesting深度学习deep-learning-tutorialdeep-neural-networksDockerhelmhelm-chartsiexiexcloudjupyterkeras
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notebooks 是用 Jupyter Notebook 编写的 AI 工具，用于人工智能方向的建模与推理。
A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet …
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lama 是用 Jupyter Notebook 编写的 AI 工具，用于人工智能方向的建模与推理。
🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
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:satellite: Simple and ready-to-use tutorials for TensorFlow
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本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。