- Python Programming
- Regression Analysis
- Dimensionality Reduction
- Decision Tree Learning
- Model Evaluation
- Logistic Regression
- Supervised Learning
- Machine Learning
- Applied Machine Learning
- Scikit Learn (Machine Learning Library)
- Classification Algorithms
- Feature Engineering
Machine Learning with Python
Completed by Jully Paola Peña Pacheco
November 28, 2020
20 hours (approximately)
Jully Paola Peña Pacheco'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
