Machine Learning with Python
Completed by Eba Kenea
September 24, 2024
20 hours (approximately)
Eba Kenea'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
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Regression Analysis
- Category: Machine Learning Algorithms
- Category: Predictive Modeling
- Category: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Scikit Learn (Machine Learning Library)
- Category: Unsupervised Learning
- Category: Python Programming
- Category: Classification Algorithms
