My friend is a student. He loves Python. He writes code every day. I am new to programming. I would like to write a program in Python. Is it easy? My friend says, "Yes! Python is simple." There are many rules, but Python isn’t hard. He shows me his code. "Can you debug this?" I ask. "Why are there errors?" He says, "Don’t worry! Debugging is part of programming." We install a new library. "Do you use this library?" I ask. "Yes! It is popular," he says. The syntax is good. Now I can write a simple program. "Are we advanced programmers yet?" I ask. He laughs. "Not yet!"
AI model training journey
English
I am a data scientist. Today, I work with AI. I import a package. The package has many modules. There is a powerful model in the library. I run the script first. The script analyzes data. It trains the model. The model isn't perfect. Why? The variables aren't correct. Should I fix them? Yes! I install the modules quickly. Now, the script runs correctly.
My friend is a developer. She asks, "Do you have any data?" I say, "Yes, here." She says, "Can I run this script?" I say, "Yes, but don't run it late." She wouldn't like errors.
Our AI model is global. It doesn't work alone. Why should we train it? Because data is important. The variables should be clean.
He asks, "Is the package installing now?" I say, "Yes! Import these modules first." They aren't hard. The code is simple.
We like this work. AI can help many people. Should we train more models? Yes! But don't run the script too fast. The data must be correct.
There is a problem. The package isn't in the library. Why? I don't know. Can you fix it? Install it here. Now the script works!
The developer says, "This model is powerful." I say, "Yes, but it needs more data." She asks, "Do you have more scripts?" I say, "No, but we can write one."
We train the model again. It analyzes the data quickly. The variables are good now. The AI works!
Should we stop? No! We should run more tests. The model isn't perfect yet. But it is learning.
The developer says, "Our AI is smart." I say, "Yes, but it doesn't know everything." She asks, "Why?" I say, "Because data is never complete."
We work late. The script runs. The model improves.
Now, the AI is ready. It can help people. Should we share it? Yes!
The end.
Writing A Python Script
English
She is writing a Python script. The script defines a function. The function processes data. She wants to compile the code now. "Can we compile this code?" she asks. He says, "Yes, but first check for errors." There is a loop in the code. The loop iterates through data. "Is the loop infinite?" she asks. "No, it isn't," he says. She prints a message on the screen: "Compiling now!" There aren't any errors. The output is fast. "Why is the output optimized?" he asks. "Because the algorithm works efficiently," she says. They call the function. The function prints new data. "Should we run this code again?" he asks. "No, we don't need to," she says. The code is correct. They are happy. Now they know how to write good code. "Don't use recursive functions here," he says. "They shouldn't be in this script." The work is done. There is no error message. The algorithm is running. "Print the output now!" she says. The screen shows the final data. They smile.
Sample flashcards 20
කේත ලිවීමට→to write code
ඔහු පයිතන් වලින් කේත ලියනවා۔→He writes code in Python.
ඇය ජාවා වලින් කේත නොලියනවා۔→She doesn't write code in Java.
ඔබ දිනපතා කේත ලියනවාද?→Do you write code every day?
සරල වැඩසටහනක්→a simple program
ඔවුන් සරල වැඩසටහනක් ලියමින් සිටී۔→They are writing a simple program.
