Machine Learning with Python: Build Real-World ML Models
Completed by Christoph Beer
March 8, 2021
20 hours (approximately)
Christoph Beer's account is verified. Coursera certifies their successful completion of Machine Learning with Python: Build Real-World ML Models
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: Unsupervised Learning
- Category: Python Programming
- Category: Model Evaluation
- Category: Machine Learning
- Category: Model Optimization
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Applied Machine Learning
- Category: Machine Learning Methods
- Category: Scikit Learn (Machine Learning Library)
- Category: Regression Analysis
