STROY OF RNN & LSTM
Imagine you have a magical weather-predicting friend named “Rehman”.
Rehman the Weather Predictor (RNN)
Rehman is pretty good at predicting the weather. He looks at today’s weather, and based on what he sees, he can guess tomorrow’s weather. For example, if it’s sunny today, Rehman might say it will be sunny tomorrow too.
- But there’s a problem: Rehman sometimes forgets things. If it’s sunny for a few days in a row, he might forget about the rainy days before that and predict sunny again.
The Smart Friend: LSTM
Now, imagine Rehman has a super smart friend named “ Luqman ”. Luqman helps Rehman remember things better. He’s like Rehman’s memory helper.
- Luqman remembers everything: Luqman keeps track of not just today’s weather, but also yesterdays, and the day before that.
- Luqman helps Rehman predict better: Using Luqman’s memory, Rehman can make better guesses about the weather. For example, if it was sunny for a few days, but it rained a lot last week, Luqman will remind Rehman about the rain, and Rehman can predict rain more accurately.
What are RNN and LSTM?
- RNN is Rehman: It’s a computer that tries to predict things based on what it sees right now.
- LSTM is Luqman: It’s a special kind of computer that helps RNN remember things better.
Together, Rehman and Luqman (RNN and LSTM) can make really good predictions!
Real-life examples:
- Predicting the weather: Just like Rehman and Luqman, computers can predict the weather based on past weather data.
- Understanding language: Computers can use RNN and LSTM to understand what you’re saying. For example, when you talk to a smart speaker, it uses RNN and LSTM to figure out what you want.
- Recognizing speech: When you talk to your phone, it uses RNN and LSTM to understand your words.
Source Code:
Github: https://github.com/programmarself/STORY-OF-RNN-AND-LSTM
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