You'll learn about Supervised vs Unsupervised Learning, look into how Statistical Modeling relates to Machine Learning, and do a comparison of each. Look at real-life examples of Machine Learning and how it affects society in ways you may not have guessed!
- Applications of Machine Learning
- Supervised vs Unsupervised Learning
- Python libraries suitable for Machine Learning
- Linear Regression
- Non-linear Regression
- Model evaluation methods
- K-Nearest Neighbour
- Decision Trees
- Logistic Regression
- Support Vector Machines
- Model Evaluation
- K-Means Clustering
- Hierarchical Clustering Density-Based Clustering
- Content-based recommender systems
- Collaborative Filtering
This course is part of the 'IBM Data Science Professional Certificate'