So far, we have explored various tools and techniques regarding web scraping via the use of the Python programming language.
Web scraping, or web harvesting, is done in order to extract and collect data from websites. Web scraping comes in handy in terms of model development, which requires data to be collected on the fly that's true, relevant to the topic, and accurate. This is desirable as it takes less time compared to implementing datasets. The data that's collected is stored in various formats, such as JSON, CSV, XML, and more, is written to databases for later use, and is also made available online as datasets.
Websites also provide web APIs with a user interface to interact with information on the web. This data can be used for research, analysis, marketing, machine learning (ML) models, information building, knowledge discovery, and more in the field...
