Basic Linear Algebra for Deep Learning – Towards Data Science

#artificialintelligence 

Linear Algebra is a continuous form of mathematics and is applied throughout science and engineering because it allows you to model natural phenomena and to compute them efficiently. Because it is a form of continuous and not discrete mathematics, a lot of computer scientists don't have a lot of experience with it. Linear Algebra is also central to almost all areas of mathematics like geometry and functional analysis. Its concepts are a crucial prerequisite for understanding the theory behind Machine Learning, especially if you are working with Deep Learning Algorithms. You don't need to understand Linear Algebra before getting started with Machine Learning, but at some point, you may want to gain a better understanding of how the different Machine Learning algorithms really work under the hood.

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