Data Extraction Techniques | Data Science| #shorts

There are many different data extraction techniques, each with its own advantages and disadvantages. Some of the most common techniques include:

Web scraping: This is the automated extraction of data from websites. It can be used to extract data from a variety of sources, including product listings, customer reviews, and social media posts.
API integration: This involves connecting to an API (application programming interface) to extract data. APIs are often used to provide access to data that is not publicly available, such as financial data or weather data.
Data crawling: This is the process of systematically visiting websites and extracting data from them. It can be used to extract data from a large number of websites, but it can be time-consuming and resource-intensive.
Data mining: This is the process of extracting patterns and insights from data. It can be used to extract data from a variety of sources, including structured and unstructured data.
Optical character recognition (OCR): This is the process of converting text from images or scanned documents into machine-readable text. It can be used to extract data from documents, such as invoices, contracts, and medical records.

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