Machine Learning with Python
Completed by Daniel Rechitsky
January 30, 2024
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: Predictive Modeling
- Category: Unsupervised Learning
- Category: Applied Machine Learning
- Category: Machine Learning
- Category: Model Optimization
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Supervised Learning
- Category: Dimensionality Reduction
- Category: Model Evaluation
- Category: Scikit Learn (Machine Learning Library)
- Category: Python Programming
