- Artificial Neural Networks
- Model Evaluation
- Supervised Learning
- Feature Engineering
- Applied Machine Learning
- Scikit Learn (Machine Learning Library)
- Machine Learning
- Classification Algorithms
- Predictive Modeling
- Regression Analysis
- Random Forest Algorithm
- Unsupervised Learning
Applied Machine Learning in Python
Completed by Lucas Vinicius Sillis do Vale
September 10, 2020
31 hours (approximately)
Lucas Vinicius Sillis do Vale'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
