Electronics Recommendation System Using Python and Scrapy

This project builds a recommendation system for electronics like mobile phones, tablets, and laptops. It uses Scrapy for web scraping, processes the data, and recommends products based on cosine similarity. A Streamlit interface makes it user-friendly.

Features

• Data Scraping: Scrapes Amazon for product data
• Data Cleaning: Handles duplicates and missing values
• Recommendation Engine: Implements cosine similarity for recommendations
• Interactive UI: Built using Streamlit

Installation and Usage

1. Install the required dependencies

   Clone the repository and navigate to the project directory, then install the dependencies listed in requirements.txt:

   git clone https://github.com/PlanetDestroyyer/Electronics-Recommendation-System-Using-Python-and-Scrapy.git
   cd Electronics-Recommendation-System-Using-Python-and-Scrapy
   pip install -r requirements.txt
   

2. Run the Scrapy Spider

   Use Scrapy to scrape product data from Amazon:

   scrapy crawl electronics_spider
   

3. Run the Streamlit app

   Start the Streamlit app to use the user interface for browsing and getting product recommendations:

   streamlit run app.py