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Deep learning in the Matrix
When talking about Deep Learning or Neural Networks, we usually face the nodes and connecting lines of the nodes. The pictures of connected nodes are visualized to explain the structure of Neural Networks. However, We don’t know what it means.
Neural Networks and Deep Learning are famous models used in various areas. This is the reason why many industries need AI engineers or data scientists who develop the models but understanding the models is a hard task. Deep learning engineers have to learn and try to understand linear algebra, calculus, and statistic which are the fundament of the deep learning model.
The Newby who start to learn deep learning usually encounters the deep learning visualization represented by connected nodes but they don’t know what it means. So, we will travel through this article to understand and learn the background of the connected nodes representation together.
Are you ready? Let’s go to the next part.
Welcome to the Matrix
A matrix is an amazing object. It can transform data into another form. It looks weird, right? Hmmm, It looks familiar to “The Matrix” movie concept. That’s RIGHT! Matrics transform some data vectors into new data vectors. How cool is that! This is a cool video that explains how a matrix transforms a vector:
