brightdatachallenge

This is a submission for the Bright Data Web Scraping Challenge: Most Creative Use of Web Data for AI Models What I Built The "Sentiment Analysis for Course Recommendation" project leverages web scraping and a robust machine learning model, featuring a Random Forest Classifier trained on the Coursera dataset, to assess courses based on user comments and sentiments, offering a more nuanced rating system beyond conventional star ratings. Users simply input the URL of a course they wish to evaluate, and the system extracts and classifies comments as positive, negative, or neutral. The resultant course rating is computed from these…

While some websites are straightforward to scrape by using just Selenium, Puppeteer, and the like, other websites that implement advanced security measures such as CAPTCHAs and IP bans may prove difficult. To overcome these challenges and ensure you can scrape 99% of websites for free using the Scraper, you will be building this in this article; you will be integrating a proxy tool in your code that will help in bypassing these security measures. However, collecting the data is just one step; what you do with that data is equally, if not more, important. Often, this requires painstakingly sifting through…