Machine Learning with Python: Build Real-World ML Models
Completed by Jonathan Eales
September 22, 2020
20 hours (approximately)
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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: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Python Programming
- Category: Applied Machine Learning
- Category: Regression Analysis
- Category: Unsupervised Learning
- Category: Machine Learning Methods
- Category: Supervised Learning
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Scikit Learn (Machine Learning Library)
