Zia Ahmad

Explore the powerful feedback loop between web scraping and artificial intelligence. While scraped web data is essential for training machine learning models, AI techniques are increasingly enhancing the efficiency, accuracy, and scalability of web scraping itself. From intelligent content extraction to anomaly detection and adaptive crawling, the fusion of these two domains is reshaping data pipelines. This session will share practical insights, real-world examples, and future possibilities at the intersection of scraping and AI.

In this presentation, Zia will explore: 

• How AI techniques (like NLP and computer vision) can enhance the accuracy and resilience of scraping pipelines;

• Ways in which scraped data powers real-world machine learning applications, including sentiment analysis, recommendation systems, and trend forecasting;

• Evaluation techniques and metrics to assess the performance of AI-enhanced scraping systems and ensure optimal data quality;

• How feedback loops can be established where scraped data improves AI models, and AI models, in turn, optimize scraping strategies.