Web Scraping for Machine Learning: Unmatched Synergy

Empower Your Machine Learning Engine with Web Scraped Data

Did you know that experts currently predict that the machine-learning market will grow at a rate of close to 40% over the next seven years? If you are linked to this market you are preparing for the future and need to make better decisions to increase your profitability. In this post, we tell you why Web Scraping is the essential fuel for Machine Learning engines in any type of business.

Today no one disputes the power of data and the explosion of AI for any business that needs to make decisions with a high level of precision, almost with a scientific basis. In this aspect, artificial intelligence with a focus on Machine Learning (ML) has become one of the main trends in the market, especially when software must be able to perform increasingly complex tasks in an automated manner.

At this point, ML models are only as good as the training and testing data. Without high-quality training data, your machine learning model could end up being ineffective and detrimental to your business.

With cutting-edge capabilities, businesses can analyze large amounts of data with speed and accuracy, allowing them to make informed decisions and stay ahead of the competition. But where do these capabilities come from and what additional services do you need to consider for your machine learning processes? Do you want to learn how to unlock the power of web data mining to stay ahead of the market?

A preliminary overview

There is no doubt that the future of data mining, including Web Scraping, will be significantly affected by the growth of the big data and machine learning market. According to the consulting firm Statista, it is estimated that the global big data market will grow by 33.8% between 2022 and 2027, reaching a value of $103 billion in 2027.

This is why companies are rapidly adopting artificial intelligence and machine learning technologies as key capabilities to drive competitive advantage. Companies are increasingly leveraging the powerful capabilities of AI and ML to automate data analysis, unlocking valuable insights that were previously inaccessible.

Unstructured data accounts for a whopping 80% of all data generated. But in their original form, they have very limited value to businesses. However, with the advancement of big data technologies, companies can now restructure such data and overcome the challenges of analyzing unstructured information.

Why Web Scraping

When we talk about Web Scraping we are referring to an automated extraction technique to collect data from websites. In this way, the essential content of a web page is downloaded, the content of that page is analyzed and the relevant data is extracted for storage or further processing. The ultimate goal is to collect large amounts of data from the Internet, in a particular way that is quickly, efficiently, and automated.

The interesting challenge of this technique, which will add value to your business, is that you can leverage web scraping to collect countless additional training data points to feed your machine learning models and integrate this mechanism into your regular work routines.

Web Scraping can be used by subject matter specialists to quickly collect data from multiple sources in a reliable manner. This data can be structured such as CSV, spreadsheets, tables; semi-structured HTML, JSON, and XML. And not structured like log files.

Fundamentals of Web Scraping for its application in ML

One of the main problems when evaluating the cost-benefit provided by web scraping solutions is to think about whether the task is carried out with an API or by hiring a professional service (see our previous post).

Data is of utmost importance. Business owners use data to spot lucrative opportunities in the market, better engage potential customers, and stay ahead. However, when collecting massive data from the web, important and difficult problems arise that a web application cannot always solve automatically.

At this point, more and more professionals and agile methodologies are needed to deal with the unstructured information of the sites, develop a platform to collect voluminous and scalable data with the flexibility that the client needs, clean the data obtained so that the processing of millions of data is as productive as possible.

At the same time, data on web pages is constantly changing and outdated data may lose its value. Specialized professionals must use the appropriate solution to monitor the information that interests us and deliver the data according to the unique needs of each client. Not to mention the complexities of maintenance and support, which require a professional team to provide the client with the necessary support.

So, the moral of all this: if you only have one API, your business will surely be very limited from the point of view of efficiency, data delivery, technical support, and scalability.

Benefits of implementing web scraping services in machine learning models

Web Scraping is an invaluable solution for efficiently collecting large amounts of model training and testing data and ultimately building your ML models. Among the main benefits of its use are:

  • Quickly obtain large amounts of data from various web sources: You will be able to create training data sets from the web that are more representative, accurate, and reliable than data sets extracted with an API or canned tool.
  • Eliminate human error: The professional services of a Web Scraping provider increase the accuracy of your data, as they can extract data from websites in an automated and precise way. As well as it will improve the presentation of this data and its understanding for efficient decision-making.
  • Reduce the cost of acquiring training data: You will surely save your business time and money by automating the extraction of web data from several different sites, instead of collecting the limited data provided by any API on the market.

Professional solutions tailored to your needs

Although integrating Web Scraping into your work process may seem complex, it is simpler than it seems: a team of professionals can give you the turnkey solution. The key is to identify what type of information you need and how to obtain it in a personalized way.

Making decisions on machine learning issues is much simpler when hiring our web scraping services. Our expertise, efficiency and adequate data processing add value to your business and will make your project more profitable.

At Scraping Pros we have years of experience leading Web Scraping projects applied to businesses and companies that implement machine learning as a central value of their business strategy. Every time a company trusts us, we give their business an advantage over their competitors.