- Supervised Learning
- Regression Analysis
- Unsupervised Learning
- Applied Machine Learning
- Dimensionality Reduction
- Machine Learning Algorithms
- Scikit Learn (Machine Learning Library)
- Classification And Regression Tree (CART)
- Statistical Analysis
- Feature Engineering
- Python Programming
- Predictive Modeling
Machine Learning with Python
Completed by EVERTON LIMA ALEIXO
September 6, 2020
20 hours (approximately)
EVERTON LIMA ALEIXO'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
