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Transcript
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SPEAKER 1
Hey everyone. I'm Chris. I am a data engineer on an AI research team. And today I just want to talk to you about neural networks. Feel like an explain like I'm five overview. So a neural network can be thought of as like a magic box. We give it some input and it gives us an output.
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So if you think of it like this way, this magic box, the neural network can be thought of like a function. If you remember from math class, the XY coordinate, the slope of a line, Y equals MX plus B. This is a function as well. Y is our output. X is our input.
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m and b are parameters of the function that's basically what this neural network is we have our input here call this x and we get our output here y except inside this function we have a lot more than just mx plus b And when we create this neural network, we don't have the parameter set right away.

What is a Neural Network?

A simple 5 minute explanation.

In this video, I’ll explain the basics of neural networks in a simple, beginner-friendly way.

We’ll look at how a neural network works, why it can be thought of as just a “magic box,” and how it learns to make predictions through training.

If you’re new to AI, machine learning, or just curious about how neural networks process information, this video is for you.

I’ll break down key concepts without getting too technical, making it easy to understand the core idea behind neural networks and how they improve with feedback.

Think of a neural network like a magic function that takes some input and then produces an output. Similar to how the function of a line works.

Follow my learning journey on GitHub

As a data engineer on an AI research team, I am learning how to build deep neural networks and sharing the journey on the way.

For my code and notes on what I am learning head to https://github.com/bitsofchris/deep-learning to follow along.

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