Artificial intelligence is the backbone of the evolving world. There is barely any sphere that has remained untouched by this evolution.
The biggest stepping stone for Artificial intelligence has been the evolution of machine learning. This refers to the use of algorithms that evolve as data is filled into the computer without any explicit instructions. This is an automated analytical process and helps the computer generate insights that we as humans are not as capable of making.
If you look at the present scenario, machine learning is the hottest emerging trend in the field of web application development as well.
We have data banks full of information that can help streamline the whole process of development and make it as user-friendly and effective as possible.
The Impact of Machine Learning
The possible applications are many in the case of web application development. If you look at the current trends, people are no longer focusing on a broader search. Instead, you have refined searches taking place. Your application needs to be able to harness this factor.
Alternative To Conventional Data Mining
Data mining is a widely used method to generate information based on the sheer volume of data that already exists.
Most websites use specialized data mining techniques like web mining to figure out existing patterns amongst the data that is available online. Enterprises now have the option to use machine learning as an alternative to conventional ways to mine data.
The way data mining can, the same way machine learning also has the capability to detect patterns based on the data available. The difference, however, between the two is that unlike data mining, Machine learning has the capability to change the program actions without the interference of humans based on the detected patterns.
Help In Understanding Customer Behaviour
The web application also has the option to use machine learning algorithms to help understand customer behavior and increase the engagement, After all, engagement is what every business wants from the web.
One of the most affected industries from this evolution in technology is the e-commerce industry. Algorithms can actually help the designers understand the features and functionality that is expected by a customer. Along with understanding the conversation around the product expected by a user.
Machine learning also helps companies design much better contact us forms. This is essential in improving the communication between customers and service providers.
The machine-learning algorithm has the ability to analyze customer queries and companies, and transfer queries to the relevant teams. This improves the overall sales and support teams and also enhance that customer experience.
Personalize The Content And Information
Facebook is a leading example of a company that uses Machine Learning effectively to personalize each user feed.
The technology employed by Facebook combines statistical analytics and predictive analysis to detect patterns based on user preferences and detected patterns. The technology identifies the pattern based on the reads and posts liked by these.
Based on that data the algorithm displays similar posts and content on the user's feed. Developers can thus embed similar machine learning technology and deliver personalized content and information according to every user's preferences.
Speedup Product Discovery
Companies like Apple and Google are leveraging machine learning algorithms for producing smart search results for each and every user. This is seen most visibly in the e-commerce websites where a search will almost every time show you an exact or at least a partial match for the searched product.
The main motive is to consistently deliver quality and relevant information to the users. The technology can also help customers choose the products that are appropriate for their needs at every given point in time. Additionally, developers can also help customers save time by only making them browse through relevant products.
Creation Of A Variety Of Machine Learning APIs
Web application developers now have the ability to streamline their work. There is a variety of open source as well as commercial machine learning APIs that can help them reach their precise goals.
These APIs have one job and that is it, to help developers accomplish tasks by the implementation of machine learning algorithms. A leading example would be the addition of specific APIs in the web code that has the ability to receive complaints and respond in real-time. The whole process would then not only be automated via the robots but would also be quick. APIs can even at some point answer phone calls directly.
Web stores can also use Machine Learning APIs to adjust the price according to the demand without human intervention.
Deal With Security Threats
Security firms have begun the implementation of technologies like logistic regression to identify malicious websites by carrying out the evaluation of thousands of websites. Some companies go a step further to use a classification algorithm to detect and predict phishing websites on the basis of criteria like security features, data encryption techniques, and domain identity.
The programmers with these initiatives can even combine multiple machine learning techniques to form a consistent checking process.
Machine learning is taking over every facet of the way websites and web applications are developed. Programmers now have the option of creating websites that are smarter than ever and have the ability to deliver strong personalized suggestions.
What web developers need to keep in mind is that the whole field is growing rapidly and thus one needs to be on their toes to ensure that the website they are handling does not fall back in terms of user experience and technology. E-commerce websites might be the kind of sites where you feel the highest amount of application of Machine learning can take place. To a certain extent, one might even be right.
The applications of machine learning are bound to vary, but that does not mean that you should just count yourself out of the loop. There are subtle ways in which one can incorporate machine learning.
From contact forms to microinteractions, everything is a new facet to explore.
