Adeniran Oluwadamilare Samue

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Well, let talk about underfitting and overfitting for today
# Imagine you're learning to draw apples.

# Underfitting is like drawing a circle and calling it an apple every time.
# It’s too simple and doesn't learn what real apples look like.

# Overfitting is like copying every tiny dot and scratch from one apple picture,
# So when you see a new apple, you don’t know it’s an apple because it looks different.

# The best way is to learn the general shape and colour of apples,
# So you can recognize any apple — even new ones!

📊 What Are "Dummies" in Data Science?
Imagine you're working on a data project and you see a column like this:

Gender

Male
Female
Male

Now ask yourself:
"How can a computer understand words like 'Male' and 'Female'?" 🤔

📌 Answer: It can’t. Computers understand numbers, not text.

So, we create something called “DUMMY VARIABLES” 💡

They turn categories into numbers like this:

Gender
_Female
_Male
_Female

1
0
1

🎉 Now, the computer can use this info for predictions!

> “Dummies” don’t mean you’re dumb 😅 — it just means you're smart enough to turn words into numbers so your machine can understand 💻✨



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16/100 days journey towards becoming a data scientist .

My first simple linear regression project took me more than two 😅 hours, guys.
Well, I predict GPA using SAT as the independent variable. All codes are in my github 👇👇👇
https://github.com/Adeniran-Oluwa
Probability ✅️
Statistics ✔️
Python basics ✔️
Simple linear regression ✔️
Multiple linear regression ⏭️

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