How Web Scraping Can Revolutionize Machine Learning?
They say that knowledge is power.
So web scraping - or data scraping - is a way to collect vast amounts of valuable data and present it effectively. And that makes you more powerful.
By specifying what you want to collect information about, an automated system will scour everything available on the public internet. Every mention, every site, every place. Imagine a google search that only returned what you wanted it to. Sounds good, right?
What about Machine Learning?
Artificial intelligence - or Machine Learning - requires data. Actually, it requires data on data on data, all of which allow process pathways to be developed.
Web scraping allows you to decide the specific parameters of a search and retrieves the information in a well-structured way. This allows the AI to “learn” about the various topics you need. From here, the process can be further automated, so that the machine develops more nuanced and useful searches.
Machine learning analyzes and ranks data based on a ‘confidence score,’ which factors into account the statistical correctness of the machine. All of this knowledge and information comes from having rich and vast data points for the device to rate its information.
This is where web scraping and AI can have a symbiotic relationship.
How Web Scraping Can Help Machine Learning
If web scraping is essential for machine learning in the beginning, then AI may just be critical to the progress of web scraping as an art form.
As the machines develop their knowledge bases - bearing in mind the speed at which the internet grows and the amounts of information which are daily added to systems - they can then suggest improvements to searches. So, where the web scraping was once the teacher, it now becomes the student.
This is why it’s vital to make sure that you have reliable data from the jump. Scrapfly can do just that, allowing you to hone and develop your data research in a way that makes the most sense for your company. With a wide range of integrations, it’s also possible to expand into processes, allowing you to build an entire data-bank for your machine learning or AI.
Web scraping is the next natural evolution of big data. The technique involves an automated system of pulling large amounts of data from websites, before putting them together in a useful manner.
If you're hoping to harness the power of information, the natural next step is looking beyond internal data to gauge the financial landscape.
Data is great. It’s useful and allows you to make informed and logical decisions. Unwieldy data is a nightmare.