- Decision Tree Learning
- Random Forest Algorithm
- Applied Machine Learning
- Artificial Neural Networks
- Python Programming
- Model Evaluation
- Classification Algorithms
- Scikit Learn (Machine Learning Library)
- Supervised Learning
- Unsupervised Learning
- Regression Analysis
- Predictive Modeling
Applied Machine Learning in Python
Completed by Daniil Vyacheslavovich Kalugin
February 9, 2024
31 hours (approximately)
Daniil Vyacheslavovich Kalugin's account is verified. Coursera certifies their successful completion of Applied Machine Learning in Python
What you will learn
Describe how machine learning is different than descriptive statistics
Create and evaluate data clusters
Explain different approaches for creating predictive models
Build features that meet analysis needs
Skills you will gain
