- Applied Machine Learning
- Scikit Learn (Machine Learning Library)
- Machine Learning
- Supervised Learning
- Decision Tree Learning
- Regression Analysis
- Statistical Modeling
- Classification And Regression Tree (CART)
- Feature Engineering
- Dimensionality Reduction
- Predictive Modeling
- Unsupervised Learning
Machine Learning with Python
Completed by MR GARETH DAVID SIMS
November 2, 2023
20 hours (approximately)
MR GARETH DAVID SIMS'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
