- Applied Machine Learning
- Feature Engineering
- Scikit Learn (Machine Learning Library)
- Predictive Modeling
- Regression Analysis
- Unsupervised Learning
- Python Programming
- Statistical Analysis
- Machine Learning Algorithms
- Dimensionality Reduction
- Supervised Learning
- Classification And Regression Tree (CART)
Machine Learning with Python
Completed by José Ernesto Morales Ventura
November 26, 2019
20 hours (approximately)
José Ernesto Morales Ventura'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
