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Stars gained: From Apr 25, 2026 to Nov 3, 2026, each from zeroStars gainedFrom Apr 25, 2026 to Nov 3, 2026, each from zero02K4KApr 25Nov 3, 2026aws/amazon-sagemaker-examplesstefan-jansen/machine-learning-for-trading
Stars: The star count at the end of each dayStarsThe star count at the end of each day10K15K20KApr 25Nov 3, 2026aws/amazon-sagemaker-examplesstefan-jansen/machine-learning-for-trading

Facts

Factaws/amazon-sagemaker-examples

Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

stefan-jansen/machine-learning-for-trading

Code for Machine Learning for Trading, 3rd edition — from data sourcing to live execution.

Stars11,00121,702
Net stars, last 30 days+21+513
Largest star day+4 on May 23, 2026+640 on Jun 2, 2026
Milestone reached in the recordNoneNone
Forks6,9425,757
LanguageJupyter NotebookJupyter Notebook
LicenseAPACHE-2.0MIT
CreatedOct 23, 2017May 9, 2018
Last pushOct 14, 2026Nov 3, 2026
ArchivedNoNo
Health facts: Maintenance3 of 4 checks3 of 4 checks
Health facts: Releases2 of 3 checks2 of 3 checks
Health facts: Security practice1 of 1 check0 of 1 check
Health facts: Community files3 of 3 checks2 of 3 checks
Commits, last 13 weeks5678
Weeks with commits, last 5212 of 5220 of 52
In the Repository Index sinceOct 22, 2026Oct 22, 2026

Topics that all of them have on the Repository Host: reinforcement-learning, machine-learning, deep-learning, data-science. The facts come from the Repository Host and from the Star History that AwesomeRepos records. A shared topic does not mean that one repository can replace another. Each Health Facts row is one dimension alone. AwesomeRepos does not add them into one score. How each check is defined

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