- Data Preprocessing
- Model Evaluation
- Supervised Learning
- Classification Algorithms
- Applied Machine Learning
- Unsupervised Learning
- Decision Tree Learning
- Regression Analysis
- Machine Learning
- Predictive Modeling
- Scikit Learn (Machine Learning Library)
- Dimensionality Reduction
Machine Learning with Python
Completed by HAMADULHAQ ANDRABI SYED
November 7, 2021
20 hours (approximately)
HAMADULHAQ ANDRABI SYED'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
