Machine Learning with Python
Completed by Daniel Bellido Alfonsin
June 27, 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: Unsupervised Learning
- Category: Supervised Learning
- Category: Model Training
- Category: Applied Machine Learning
- Category: Statistical Methods
- Category: Predictive Modeling
- Category: Machine Learning Algorithms
- Category: Logistic Regression
- Category: Regression Analysis
- Category: Scikit Learn (Machine Learning Library)
- Category: Model Evaluation
- Category: Model Optimization
