- Regression Analysis
- Applied Machine Learning
- Machine Learning
- Classification Algorithms
- Supervised Learning
- Decision Tree Learning
- Scikit Learn (Machine Learning Library)
- Unsupervised Learning
- Predictive Modeling
- Python Programming
- Model Evaluation
- Dimensionality Reduction
Machine Learning with Python
Completed by RAPHAEL NGIGI WANJIKU
March 18, 2022
20 hours (approximately)
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What you will learn
Explain key concepts, tools, and roles involved in machine learning, including supervised and unsupervised learning techniques.
Apply core machine learning algorithms such as regression, classification, clustering, and dimensionality reduction using Python and scikit-learn.
Evaluate model performance using appropriate metrics, validation strategies, and optimization techniques.
Build and assess end-to-end machine learning solutions on real-world datasets through hands-on labs, projects, and practical evaluations.
Skills you will gain
