- Model Evaluation
- Python Programming
- Classification Algorithms
- Regression Analysis
- Scikit Learn (Machine Learning Library)
- Dimensionality Reduction
- Decision Tree Learning
- Applied Machine Learning
- Unsupervised Learning
- Supervised Learning
- Predictive Modeling
- Logistic Regression
Machine Learning with Python
Completed by PATEL KHUSHIBEN BHAGWANBHAI
February 18, 2024
20 hours (approximately)
PATEL KHUSHIBEN BHAGWANBHAI'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
