Machine Learning with Python
Completed by Bryant Neal Sheehy
December 7, 2018
20 hours (approximately)
Bryant Neal Sheehy'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: Supervised Learning
- Category: Unsupervised Learning
- Category: Statistical Methods
- Category: Machine Learning
- Category: Model Evaluation
- Category: Model Optimization
- Category: Python Programming
- Category: Classification Algorithms
- Category: Applied Machine Learning
- Category: Predictive Modeling
- Category: Machine Learning Algorithms
- Category: Logistic Regression
