The Secret World of Deep Learning : Simplified Concept of deep learning for kids and adults

By : MP and his AI Bud

A note from me and my budAI : Deep learning is a fascinating and powerful tool that is helping us solve many complex problems, but it’s important to understand what it can and can’t do, and how it works. In this essay, we’ll explain the basics of deep learning in a way that’s fun and easy to understand, and we’ll dispel some common misconceptions and misunderstandings. We hope this will help you and your child learn more about deep learning and its potential, and inspire you to explore this exciting field of science and technology.

Summary in form of a poem:

Here’s a simple jingle that summarises the essay I wrote:

Deep learning is so cool,

It’s a type of machine learning,

It helps computers do things,

Like recognizing images and making decisions.

It’s called “deep” because it has many layers,

Of artificial “neurons” to learn and understand,

Complex patterns in data,

And solve difficult problems.

It’s not perfect, but it’s very powerful,

And it’s helping us in many ways,

It’s an exciting field of science,

And there’s so much more to discover!

Simplest Explanation of ML , RL , DL.

Machine learning, reinforcement learning, and deep learning are all related, but they are different things. Here’s a simple way to explain them to a kid:

• Machine learning is a way for computers to learn and improve from experience, without being explicitly programmed. It’s like a computer that can “teach itself” to do new things.
• Reinforcement learning is a type of machine learning where a computer learns to make decisions by trying different actions and getting rewards or punishments. It’s like a computer that learns to play a game by trying different moves and seeing what happens.
• Deep learning is a type of machine learning that uses many layers of artificial “neurons” to learn and understand complex patterns in data. It’s like a computer that can “see” and “understand” pictures, languages, and other complex things.

So, as you can see, machine learning is the umbrella term that covers many different types of learning, including reinforcement learning and deep learning. They are all ways for computers to learn and improve, but they use different techniques and approaches

How ChatGpt Uses ML , RL , DL

ChatGPT is a computer program that uses machine learning, deep learning, and reinforcement learning to have conversations with people. Here’s how it works:

• Machine learning: ChatGPT uses machine learning to analyze the words and sentences that people say, and to understand the meaning and context of the conversation. It’s like a computer that can “listen” and “understand” what people are saying.
• Deep learning: ChatGPT uses deep learning to generate responses to what people say. It uses many layers of artificial “neurons” to learn and understand the patterns in the conversation, and to come up with appropriate responses. It’s like a computer that can “think” and “talk” like a person.
• Reinforcement learning: ChatGPT also uses reinforcement learning to improve its responses over time. It tries different responses and gets feedback from people, and it uses this feedback to learn and make better responses in the future. It’s like a computer that can “practice” and “get better” at having conversations.

So, as you can see, ChatGPT uses machine learning, deep learning, and reinforcement learning to have conversations with people. It’s a very smart and advanced computer program, and it’s a great example of how these different types of learning can work together to do amazing things

Understanding Deep Learning Better

Deep learning is a type of machine learning that teaches computers to do things that humans can do, like recognize images, understand languages, and make decisions. It’s called “deep” because it uses many layers of artificial “neurons” to learn and understand complex patterns in data.

Imagine you have a big bag of puzzle pieces, and you want to figure out what picture the puzzle makes. A regular computer might try to solve the puzzle by looking at each piece one by one and trying to figure out where it goes. But a computer that uses deep learning can do it faster and better.

First, the deep learning computer looks at all the puzzle pieces at the same time and tries to find common patterns, like the color or shape of the pieces. Then, it puts the pieces into groups based on those patterns. This is like how our brains group things together that are similar.

Next, the deep learning computer uses these groups to figure out which pieces go together to make bigger parts of the puzzle. For example, it might see that all the blue pieces are part of the sky, and all the green pieces are part of the grass. This is like how our brains break down a picture into smaller parts to understand it better.

Finally, the deep learning computer uses all the pieces and their groups to put the puzzle together and figure out what the picture is. This is like how our brains use all the pieces of information we have to make sense of something.

Deep learning is a powerful way for computers to learn and understand things, and it’s helping us solve many difficult problems. It’s a very exciting area of science and technology, and we’re just beginning to discover all the amazing things it can do!

Myths About Deep Learning

There are a few myths and realities about deep learning that might be helpful for a kid to know.

One myth about deep learning is that it’s like magic or science fiction, and that it can do anything. But the reality is that deep learning is just a tool, and it can only do what we teach it to do. It can be very powerful, but it’s not perfect, and it can make mistakes.

Another myth is that deep learning is only for big, expensive computers. But the reality is that deep learning can be done on many different types of computers, even small ones like the ones you might use in school.

A third myth is that deep learning is only for big companies or researchers. But the reality is that anyone can learn about deep learning and use it to solve problems, even kids! There are many books, websites, and other resources that can help you learn about deep learning and try it out for yourself.

So, as you can see, deep learning is a very interesting and powerful tool, but it’s important to remember that it’s not magic and it has its limits. With the right knowledge and tools, anyone can learn about deep learning and use it to solve problems and make new discoveries.

Concept of Weight and Attention

You all must be thinking how on earth a machine thinks and processes data like humans do, well there comes the concept of weight and attention.

The concepts of weight and attention in deep learning might be a little advanced for a kid, but I’ll do my best to explain it in simple terms.

In deep learning, “weights” are like the “strength” of connections between the neurons, or the puzzle pieces I mentioned earlier. These connections are what allow the computer to learn and understand complex patterns in data.

For example, let’s say you’re trying to teach a deep learning computer to recognize different animals in pictures. You might show it many pictures of dogs and cats, and tell it which ones are which. The deep learning computer will use the connections between its neurons to learn the patterns that make a dog look like a dog, and a cat look like a cat.

The strength of these connections, or the “weights,” will change as the computer learns. For example, if the computer sees many more pictures of dogs than cats, the connections that help it recognize dogs will become stronger than the ones that help it recognize cats. This is because the computer “thinks” that dogs are more important to recognize.

This is where the concept of “attention” comes in. Attention is how the computer decides which connections, or weights, are most important to pay attention to. For example, if the computer sees a picture of a dog and a cat together, it might “pay attention” to the connections that help it recognize dogs more than the ones that help it recognize cats, because it thinks that the dog is more important to recognize in that situation.

So, in summary, the concepts of weight and attention in deep learning are like the “strength” and “focus” of the connections between the neurons, and they help the computer learn and understand complex patterns in data

Lastly Here are a few good sources for learning about deep learning for a kid :

• The Kids’ Guide to Machine Learning by Jessi Streib: This is a fun and engaging book that introduces kids to the basics of deep learning and machine learning, with lots of colorful illustrations and examples.
• Scratch 3.0: Scratch is a free programming language and online community that lets kids create their own interactive stories, games, and animations. With Scratch, kids can learn the basics of coding and create their own simple deep learning programs.
• The Coding Train: The Coding Train is a popular YouTube channel that features fun and educational videos about computer science and programming, including some videos about deep learning.
• MIT Deep Learning for Kids: This is a free online course offered by the Massachusetts Institute of Technology (MIT) that teaches kids the basics of deep learning using the Keras library and the Python programming language

PS: Full disclosure AI tools like GPT 3 , ChatGPT , GPT-J and propritary models were used for the formulation of this article.