1.10 Traditional ML with Python packages

Key points

1. NVIDIA's scikit-learn glossary defines an estimator as the core machine-learning algorithm that fits the training data to produce a model.

   What NVIDIA says (1)

   “An estimator is the core machine learning algorithm that fits the training data to produce a model.”

   — What is scikit-learn?

2. Pipelines chain transformers and estimators so preprocessing, training and prediction stay consistent, which makes workflows reproducible.

   What NVIDIA says (1)

   “Pipelines in scikit-learn chain transformers and estimators into a cohesive workflow, ensuring consistent preprocessing, training, and prediction steps.”

   — What is scikit-learn?

3. NVIDIA's scikit-learn glossary names principal component analysis (PCA) as a dimensionality-reduction technique that reduces the number of variables while retaining meaningful patterns.

   What NVIDIA says (1)

   “For datasets with many features, dimensionality reduction techniques, such as PCA, can simplify the input data by reducing the number of variables while retaining meaningful patterns.”

   — What is scikit-learn?

Key terms

• scikit-learn: Python library for traditional machine learning.
• Principal component analysis: A dimensionality-reduction technique that keeps meaningful patterns with fewer variables.

Sample question

In scikit-learn, what is an estimator?