- Logistic Regression
- Feature Engineering
- Python Programming
- Scikit Learn (Machine Learning Library)
- Applied Machine Learning
- Unsupervised Learning
- Regression Analysis
- Decision Tree Learning
- Machine Learning
- Model Evaluation
- Supervised Learning
- Dimensionality Reduction
Machine Learning with Python
Completed by Luis Enrique Santos Vereau
January 11, 2024
20 hours (approximately)
Luis Enrique Santos Vereau's account is verified. Coursera certifies their successful completion of Machine Learning with Python
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
