Introduction to Machine Learning for Data Scientists — Data Science R…
Enough ML to know when it's the right tool and how to use it responsibly
Steps in Introduction to Machine Learning for Data Scientists
- When to Use Machine Learning vs Simple Analysis — advanced · Recognizing when a well-designed query or chart beats a model, and vice versa
- Regression Basics for Data Scientists — advanced · Predicting a continuous outcome and interpreting the resulting model
- Classification Basics for Data Scientists — advanced · Predicting a category and understanding what the model's probability output means
- Clustering for Segmentation — advanced · Grouping similar customers or items without predefined labels
- Model Evaluation Basics — advanced · Enough evaluation literacy to sanity-check whether a model is any good
Part of
- Data Science roadmap — the full learning path