What are the applications of dimensionality reduction in machine learning?
An example of an AI chatbot conversation about applications of dimensionality reduction in ML.
What are the applications of dimensionality reduction in machine learning?
Dimensionality reduction is used to simplify models, improve visualization, and enhance performance in ML tasks.
Can you give me some specific examples of where it's applied?
Sure! It's commonly used in image processing, natural language processing, and genomics.
How does it help in image processing?
In image processing, it reduces the number of pixels while retaining essential features, speeding up processing.
What techniques are commonly used for dimensionality reduction?
Common techniques include PCA (Principal Component Analysis), t-SNE, and UMAP.
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