- Scikit Learn (Machine Learning Library)
- Dimensionality Reduction
- Model Evaluation
- Python Programming
- Regression Analysis
- Unsupervised Learning
- Classification Algorithms
- Supervised Learning
- Decision Tree Learning
- Machine Learning
- Applied Machine Learning
- Feature Engineering
Machine Learning with Python
Completed by Mónica Rafaela da Cruz Mota Ferreira
January 24, 2021
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
