- Classification Algorithms
- Predictive Modeling
- Feature Engineering
- Machine Learning
- Regression Analysis
- Model Evaluation
- Python Programming
- Applied Machine Learning
- Logistic Regression
- Dimensionality Reduction
- Scikit Learn (Machine Learning Library)
- Supervised Learning
Machine Learning with Python
Completed by RICARDO DANIEL REYES ARELLANO
February 7, 2020
20 hours (approximately)
RICARDO DANIEL REYES ARELLANO'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
