Machine Learning with Python: Build Real-World ML Models
Completed by Jairo Andrés Hernández Mosquera
November 20, 2019
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: Machine Learning Methods
- Category: Supervised Learning
- Category: Applied Machine Learning
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Model Evaluation
- Category: Model Optimization
- Category: Machine Learning
- Category: Python Programming
- Category: Regression Analysis
- Category: Unsupervised Learning
- Category: Scikit Learn (Machine Learning Library)