- Supervised Learning
- Classification Algorithms
- Model Evaluation
- Applied Machine Learning
- Scikit Learn (Machine Learning Library)
- Python Programming
- Feature Engineering
- Unsupervised Learning
- Logistic Regression
- Machine Learning
- Decision Tree Learning
- Dimensionality Reduction
Machine Learning with Python
Completed by Neema Maharjan
July 17, 2020
20 hours (approximately)
Neema Maharjan'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
