- Predictive Modeling
- Scikit Learn (Machine Learning Library)
- Logistic Regression
- Unsupervised Learning
- Machine Learning
- Supervised Learning
- Dimensionality Reduction
- Regression Analysis
- Decision Tree Learning
- Classification Algorithms
- Applied Machine Learning
- Model Evaluation
Machine Learning with Python
Completed by Muslim Riyad Al-Issa
June 30, 2024
20 hours (approximately)
Muslim Riyad Al-Issa'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
