In this article, I would like to dig deeper into the structural differences between Machine Learning and Deep Learning algorithms, so that you can understand what is their key difference and how to spot them.
One of the first problems a beginner data scientist faces is understanding the difference between Deep Learning and Machine Learning. In general, Machine Learning englobes the entire world of AI, while Deep Learning is a sub-category of Machine Learning. However, this does not give you any valuable insight. In this article, I would like to dig deeper into the structural differences between Machine Learning and Deep Learning algorithms, so that you can understand what is their key difference and how to spot them.
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The past few decades have witnessed a massive boom in the penetration as well as the power of computation, and amidst this information.
“You do not really understand something unless you can explain it to your grandmother” Not sure where this quote originally came from, it is sometimes kind of half-attributed to Albert Einstein.
Deep Learning Explained in Layman's Terms. In this post, you will get to learn deep learning through a simple explanation (layman terms) and examples.
This post provides the details of the architecture of Convolutional Neural Network (CNN), functions and training of each layer, ending with a summary of the training of CNN.