Among other purposes, web scraping is used for collecting custom datasets for machine learning tasks, mostly for model training.
There are a lot of ready-to-use datasets you can download or buy from the web. But quite often, data scientists need to collect custom data for their machine learning projects.
The first reason is that data gets outdated very quickly, and datasets should be used just after they are created. The second reason is that machine learning projects require specificity. Despite millions of existing datasets you can find on Kaggle or Google, it’s still very difficult to find exactly what you need.
It is far simpler to order data from a reliable data pipeline than to spend hundreds paying data scientists to collect and prepare datasets manually.Another important thing is the development of a data pipeline to set continuous data feed. As training machine algorithms is often an incessant process, reliable data delivery on a regular basis is necessary.
At DivaBizTech, we build data pipelines with quality assurance and data cleansing at each stage.
The most important nuance you should pay attention to is the quality of the web source you want to scrape. As you know, the success of the machine learning process depends on the quality of input data. We as a data scraping company do data quality assurance (QA).
We check data with automated custom software and manually with our QA department according to the specific rules guided by your project’s needs.
While we test for data integrity to make sure that all of your data is scraped properly, we can’t check the quality of the web source itself. You choose the web sources, and we scrape the needed data.
Another big step is data cleansing. We perform this process with the help of rules you set for your task.
One of our clients is a company that focuses on content marketing using artificial intelligence technologies. Based on machine learning technologies, they define the best content for other businesses’ target audiences. They requested scraping of more than 10 million websites to analyze different parameters and implement a machine learning algorithm. We scraped all the data for this project over three weeks, cleansed it, and provided it to our client. You can find his feedback in our testimonials!
If you need custom datasets for your project, schedule a free consultation with our web scraping expert to talk about your project and get a quote!
