How Machine Learning Algorithms work under the hood is an aspect not understood by many. What does a layer of CNN see? How backpropagation works,? How exactly are the weights updated in a layer? These are some of the questions that pop in our minds time and again. These concepts can be particularly overwhelming for the beginners who want to have a hard time in aligning mathematical equations with the theory. The good news is that some people understand this pain and want to provide alternative forms of learning. This article is a compilation of five such tools that go beyond the theory and instead present intuitively explanations of the standard machine learning concepts.

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