A recommender system is a powerful tool in machine learning, often used in e-commerce, streaming platforms, and social media. Below is a simple implementation using collaborative filtering with Python and scikit-surprise.

📋 Step-by-Step Code

1. Install Dependencies

pip install scikit-surprise

2. Load Dataset

from surprise import Dataset
data = Dataset.load_builtin('ml-100k')  # Example dataset

3. Train Model

from surprise import KNNBasic
sim_options = {'name': 'cosine', 'user_based': True}
model = KNNBasic(sim_options=sim_options)
model.fit(data)

4. Make Predictions

from surprise import accuracy
predictions = model.test(data)
accuracy.rmse(predictions)  # Evaluate performance

📌 Project Resources

📈 Visualizing the Process

Machine_Learning
Recommender_System