Data Science and Machine Learning (Theory and Projects) A to Z - Feature Engineering: Activity-Feature Scaling

The video tutorial discusses dimensionality reduction, focusing on feature selection and extraction methods. It highlights the limitations of traditional methods when applied to big data, characterized by high dimensionality and numerous sample points. The instructor encourages exploring these limitations to develop new algorithms, presenting it as a hot research topic. The course concludes with a motivational note for future learning.

What motivates researchers to explore dimensionality reduction in the context of big data?

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In what ways can exploring the limitations of traditional methods lead to new algorithm development?

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