Large-scale data gathering is a difficult and multilayered process. It requires a lot of resources and high-level technical knowledge. It only seems reasonable to find a more manageable solution to aid in this process.
Favorably, recent advancements in computing solutions allowed AI and ML to become reliable sources for large-scale use. Taking this as an advantage, Oxylabs has dedicated its time to create an AI and ML-based solution that automates data gathering to a certain level – Next-Gen Residential Proxies.
The application of AI and ML in large-scale data gathering operations is a topic that requires an in-depth dive in. For this reason, we have written an extensive white paper thoroughly going over the overall definitions of AI, ML, and Deep learning, and how it can be applied to web scraping.
What can you expect from this white paper?
In this white paper, you’ll learn:
- The terminology of AI applications, ML algorithms, and Deep Learning – all terms are intertwined and often used together, though they have different meanings.
- The basic concept of AI – it is the idea of building machines or computers that are capable of thinking like humans.
- What is Machine Learning – a practice of using different algorithms to parse data, learn from it, and then decide or predict something in question.
- What is Deep Learning – it attempts to arrive at conclusions in a similar manner to humans by analyzing data with a logical structure.
- Web scraping’s value chain and its main challenges.
- How creating an AI and ML-powered solution will simplify the data gathering pipeline – this will take care of proxy pool management, data parsing maintenance, and other repetitive work.
- What are Next-Gen Residential Proxies – powered by the latest AI and ML innovations it is a new Oxylabs solution built with heavy-duty data retrieval operations in mind.
Download our extensive white paper and learn more on the application of AI and ML in large-scale data gathering operations: