How Machine Learning Has Helped Web Development Evolve

Artificial Intelligence (AI) is quickly becoming the backbone of the modern evolving world. We have seen increasing sophistication in the development of smartphones as well as web and mobile apps. Their intuitive operations have changed the very fabric of our experience on the internet.

This article will focus on Machine Learning (ML)’s contributions in refining web development.

1. Efficient Alternative to Data Mining

We all know how data mining is extensively used to produce general information and patterns from large data. A lot of websites use specialized data mining techniques, such as web mining, to determine the patterns among existing data that is available online.

Today enterprises can now make use of ML as an alternate means to mining data. In fact, machine learning development provides far more refined and sophisticated means to mine, analyse and understand data.

2. Understanding Consumer Behaviour

Web apps can now make use of ML algorithms to discern consumer behaviour and improve their engagement. E-commerce has leveraged this and online retailers have employed ML algorithms in order to refine their user engagement and improve their sales.

These algorithms provide deep insights into the customer’s psyche.
Additionally, they also help in analysing customer queries before being passed on to the appropriate department.

ML development has effectively enhanced the level and quality of communication between the users and web apps by making them highly intuitive.

3. Deeper Personalization

Facebook is the best example of a platform that has successfully employed ML and artificial intelligence to provide deep personalization.

User patterns are detected on the basis of their likes, reactions, and associations. Statistical and predictive analysis is employed on these patterns to provide each user with a customized feed.

This is a revolutionary concept. Today, developers can embed similar algorithms in their web apps and provide each user with content and information that is catered to them.

4. Development of Machine Learning APIs

Thanks to various public and commercial machine learning APIs that are readily available, developers can streamline their web apps.

These APIs help implement machine learning algorithms and refine web app functions. One great example of this is the employment of APIs in the web code that helps receive complaints and provide response in real-time. The entire process is automated and the response time is faster than ever.

Today, web stores are using some of these APIs to regulate their catalog prices according to market demands without any human assistance.

5. Improved Security

Machine learning web development, along with artificial intelligence, has strengthened security features using sophisticated algorithms.

Technologies such as logistic regression are employed to track down malicious websites by evaluating thousands of sites. Many companies are using classification algorithms in order to identify phishing websites on criteria such as data encryption techniques and domain identity.

Combining these techniques with various Machine learning techniques can help form a consistent and thorough process of checks.

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