📊 DSA Progress Prediction using Simple Linear Regression

This project uses Simple Linear Regression to predict how many problems can be solved based on the number of days of practice.

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🚀 Project Idea

The goal of this project is to understand and implement a basic Machine Learning model that predicts:

📈 Number of problems solved (output)
based on
⏳ Number of days practiced (input)

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🧠 Concepts Used

• Simple Linear Regression
• Data Visualization (Matplotlib)
• Train-Test Split
• Model Training & Prediction

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📂 Dataset

The dataset is manually created and represents a learning pattern over time.

Days	Problems Solved
1	1
2	6
4	10
...	...

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⚙️ Tech Stack

• Python 🐍
• Pandas
• NumPy
• Matplotlib
• Scikit-learn

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📈 Model Workflow

1. Load dataset using Pandas
2. Split data into training and testing sets
3. Train model using LinearRegression()
4. Visualize results using scatter plot + regression line
5. Predict future outcomes

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🔮 Example Prediction

model.predict([[23]])