In this post, you will discover a gentle introduction to dimensionality reduction for machine learning

After reading this post, you will know:

• Large numbers of input features can cause poor performance for machine learning algorithms.
• Dimensionality reduction is a general field of study concerned with reducing the number of input features.
• Dimensionality reduction methods include feature selection, linear algebra methods, projection methods, and autoencoders.

#machine-learning