Machine Learning with Python
Completed by JAE KIL CHA
March 4, 2020
20 hours (approximately)
JAE KIL CHA'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: Dimensionality Reduction
- Category: Model Training
- Category: Logistic Regression
- Category: Predictive Modeling
- Category: Machine Learning Algorithms
- Category: Supervised Learning
- Category: Machine Learning Methods
- Category: Applied Machine Learning
- Category: Unsupervised Learning
- Category: Scikit Learn (Machine Learning Library)
- Category: Regression Analysis
- Category: Statistical Methods
