Machine Learning with Python: Build Real-World ML Models
Completed by Johany Andrés Carmona Chaverra
September 13, 2019
20 hours (approximately)
Johany Andrés Carmona Chaverra'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: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Machine Learning Methods
- Category: Unsupervised Learning
- Category: Python Programming
- Category: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Applied Machine Learning
- Category: Regression Analysis
- Category: Scikit Learn (Machine Learning Library)
