- Unsupervised Learning
- Supervised Learning
- Machine Learning Algorithms
- Regression Analysis
- Classification And Regression Tree (CART)
- Machine Learning
- Scikit Learn (Machine Learning Library)
- Statistical Analysis
- Applied Machine Learning
- Python Programming
- Feature Engineering
- Dimensionality Reduction
Machine Learning with Python
Completed by SWASTIK SOURAV SAHOO
September 5, 2020
20 hours (approximately)
SWASTIK SOURAV SAHOO'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
