Machine Learning with Python
Completed by RAEMUS RAMPAUL
August 25, 2024
20 hours (approximately)
RAEMUS RAMPAUL'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: Regression Analysis
- Category: Scikit Learn (Machine Learning Library)
- Category: Applied Machine Learning
- Category: Machine Learning Algorithms
- Category: Dimensionality Reduction
- Category: Classification Algorithms
- Category: Unsupervised Learning
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Model Training
- Category: Model Evaluation
- Category: Model Optimization
