MF

Ryota-Kawamura/Mathematics-for-Machine-Learning-and-Data-Science-Specialization

Master the Toolkit of AI and Machine Learning. Mathematics for Machine Learning and Data Science is a beginner-friendly Specialization where you’ll learn the fundamental mathematics toolkit of machine learning: calculus, linear algebra, statistics, and probability.

811 342 +0/wk
GitHub
bayesian-statistics calculus determinants eigenvalues-and-eigenvectors gradient-descent linear-algebra linear-equation linear-regression machine-learning mathematical-optimization mathematics probability
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Ryota-Kawamura/Mathematics-for-Machine-Learning-and-Data-Science-Specialization has +0 stars this period . 7-day velocity: -0.1%.

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Metric Mathematics-for-Machine-Learning-and-Data-Science-Specialization DeepMCPAgent generate-subtitles caer
Stars 811 811811810
Forks 342 126114108
Weekly Growth +0 +0+0+0
Language Jupyter Notebook PythonJavaScriptPython
Sources 1 111
License N/A Apache-2.0N/AMIT

Capability Radar vs DeepMCPAgent

Mathematics-for-Machine-Learning-and-Data-Science-Specialization
DeepMCPAgent
Maintenance Activity 0

Last code push 1004 days ago.

Community Engagement 20

Fork-to-star ratio: 42.2%. Active community forking and contributing.

Issue Burden 70

Issue data not yet available.

Growth Momentum 30

No measurable growth in the current period (first-day cold start expected).

License Clarity 30

No clear license detected — proceed with caution.

Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.