本文介绍了降维技术的重要性和应用场景，如数据压缩、提高学习算法的速度及帮助理解数据。特别聚焦于主成分分析（PCA）这一核心方法。
Dimensionality Reduction
——allows us to compress the data and have it therefore use up less computer memory or disk space, but it will also allow us to speed up our learning algorithms.
——to visualize the data,helps us to develop effective learning algorithms, if we can understand our data better.
principle components analysis (PCA)
Among this:
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