- Applied Machine Learning
- Regression Analysis
- Supervised Learning
- Unsupervised Learning
- Decision Tree Learning
- Model Evaluation
- Feature Engineering
- Predictive Modeling
- Python Programming
- Machine Learning
- Dimensionality Reduction
- Logistic Regression
Machine Learning with Python
Completed by Mohammad Saleh Ebrahimi Shahabadi
August 19, 2020
20 hours (approximately)
Mohammad Saleh Ebrahimi Shahabadi'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
