Data Engineer at Oxylabs
Andrius is a Data Engineer with 5+ years of experience at Oxylabs. During this time, he played a crucial role in numerous projects, implementing a variety of features, including ML, to enhance web scraping product pipelines. He is currently at the forefront of developing a new data-based product and uses his extensive expertise for anything from data engineering to integrating innovative ML functionalities. His broad experience and continuous interest in the machine learning field should offer unique perspectives on leveraging ML for web scraping.
Can web scraping still be done without ML? Perhaps, but for large-scale operations, we need to turn to something more potent. Especially if we want data gathering to be quick and efficient. In this presentation, Andrius explores the intersections between web scraping and ML. He will provide an insightful overview of its practical uses for such things as adaptive parsing, scraper block detection, and more. He will also consider the future possibilities of ML for such areas as product matching across e-commerce platforms and website similarity detection for parsing templates.
Join his lesson to learn about:
How do scrapers use ML to outsmart anti-bot systems and vice versa?
What’s the role of web scraping for ML training?
How can large language models be used in advanced parsing?
Coming from different industries and backgrounds but united in common passion and aspirations, these web scraping experts will share their experiences and answer your questions.
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