Anri-Lombard/Coursera-Machine-Learning-Specialization-2022

Learning Fundamentals of Machine Learning all over along with Stanford's Andrew Ng

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This project offers personal notes and interpretations of Stanford's Andrew Ng's Machine Learning Specialization, covering foundational concepts like supervised and unsupervised learning, regression, and classification. It helps learners grasp machine learning fundamentals, understand different algorithms, and apply them to real-world problems. The resource is ideal for individuals (students, professionals, or self-learners) looking to acquire or deepen their understanding of machine learning.

No commits in the last 6 months.

Use this if you are taking a machine learning course and need supplementary notes, explanations, and examples to reinforce your understanding of core concepts like regression, classification, and gradient descent.

Not ideal if you are looking for ready-to-use code, a specific machine learning application, or a deep dive into advanced research topics rather than foundational learning materials.

Machine Learning Education Data Science Learning Predictive Modeling Fundamentals Algorithm Understanding
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 18 / 25

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Jupyter Notebook

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Last pushed

Jun 08, 2023

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