- Machine Learning
- Scikit Learn (Machine Learning Library)
- Regression Analysis
- Predictive Modeling
- Machine Learning Algorithms
- Supervised Learning
- Statistical Analysis
- Feature Engineering
- Applied Machine Learning
- Classification And Regression Tree (CART)
- Unsupervised Learning
- Python Programming
Machine Learning with Python
Completed by James M. Comstock
March 24, 2020
20 hours (approximately)
James M. Comstock'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
