Machine Learning with Python
Completed by Daniel Evan Akin
November 2, 2019
20 hours (approximately)
Daniel Evan Akin's account is verified. Coursera certifies their successful completion of Machine Learning with Python
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: Model Training
- Category: Unsupervised Learning
- Category: Logistic Regression
- Category: Statistical Methods
- Category: Predictive Modeling
- Category: Machine Learning Algorithms
- Category: Applied Machine Learning
- Category: Dimensionality Reduction
- Category: Regression Analysis
- Category: Scikit Learn (Machine Learning Library)
