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Machine learning training
Machine learning techniques are meant to equip machines with the ability to learn and develop by providing them with training data. The data used as training data could vary depending on individual cases. However, web data is ideal for training machine learning models for a wide range of use cases. With training data sets, machine learning models can be developed to do correlational tasks like classification, clustering, attribution etc. Since the performance of a machine learning model will depend on the quality of training data, it is important to crawl only high quality sources.
Why web scraping for training data
When it comes to aggregating relevant data at scale, web scraping comes out as the best route forward. This is because of the capability it provides to efficiently extract large amounts of data from targeted sources. Speed of extraction is also another key differentiator in this context.
How web scraping for training data works
While going with a dedicated web scraping provider like PromptCloud, you can skip the challenges and technical complexities involved in web data extraction. Here is how a dedicated web scraping service works:
You reach out to us with the your requirement specifics including:
Once we receive the requirements, our team will setup the crawlers to extract the data from the target sites. You have the flexibility of choosing the data delivery format and method. Being a fully customizable solution, we can provide the data in CSV, JSON or XML and via Amazon S3, Dropbox, Box, FTP and PromptCloud API.
Benefits of choosing PromptCloud’s web scraping service for training data
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