- Feature Engineering
- Unsupervised Learning
- Decision Tree Learning
- Logistic Regression
- Regression Analysis
- Predictive Modeling
- Supervised Learning
- Python Programming
- Model Evaluation
- Scikit Learn (Machine Learning Library)
- Classification Algorithms
- Machine Learning
Machine Learning with Python
Completed by MARCEL GONZALEZ RODRIGUEZ
April 24, 2022
20 hours (approximately)
MARCEL GONZALEZ RODRIGUEZ'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
