Introduction:
Machine learning is a part of Artificial intelligence (AI) and is one of the most important technology enhancements during the past decade. It is a learning technique that provides machine the capability to automatically learn and upgrade from experience. Machine learning (ML) is achieved by developing such computer programs that can access data and then use it to memorize for themselves.
Examples
Speech recognition i.e. speech-to-text processing is a perfect example of an application of machine learning that can also be used for data entry thereby saving the precious time. We can also see speech recognition via Google voice search. Not only Machine Learning but also there are many ways even Artificial Intelligence impacts our day to day life.
Programming languages:
Python, Prolog. Java and Lisp are the most commonly used programming languages for machine learning. Among these, Python is considered to be the best due to its simple syntax.
Many companies are using a machine learning technique for their internal CMS & to serve their customers in a better manner. This article focuses on the major social media sites using this technology and its advantages.
Top social media sites:
Instagram, one of the most popular images sharing platforms has modified itself with the help of DeepText (Facebook’s learning-based text understanding engine that can grasp the content of thousands of posts per second very accurately. It helps Instagram’s system to detect fake accounts and clean their spam/abusive comments and videos. This enables users to see only the elegant posts. Now the users have to only turn on manual filters in their account settings if they wish to activate any kind of abusive comment functionality.
Twitter has used machine learning to initiate the grade in image cropping. With the help of investigators data, Twitter networks can now easily predict the image areas of user’s interest like faces, text and other parts. This helps the users to crop the images very quickly as they are uploaded resulting in better user experience. Whether you choose to see the “best tweets first” or ‘tweets in chronological order”, these variations are actually driven by machine learning technology.
Reddit, also known as the front page of the internet, a vibrant hub of internet news, videos, images, and various kinds of posts use ML to improve its site search results, to index the new posts and also update their relevant signals in real time based upon comments/votes, etc. ML also enabled Reddit to make its search even faster and easy to align with the platform’s growth. Moreover, the number of machines required for search operations also reduced to 30 from 200 and there was around 33% increase in the number of posts indexed.
Pinterest used ML to enhance its content discovery by acquiring a machine learning company called Koesi. This is quite obvious because the major function of Pinterest is to organize existing content. ML also enabled Pinterest to implement functions like spam moderation and minimizing the agitate of email newsletter subscribers.
Facebook enhanced its messenger service by ML. Messenger is like an experimental testing laboratory for chatbots. Now any developer can develop and submit his chatbot for including in Facebook messenger i.e. companies looking to provide better customer services and preservation can also control chatbots even if they have less or limited technology resources. ML also lets Facebook to automatically detect and remove spam, abusive/offensive content. ML is also able to detect posts highlighting a suicidal tendency and process such panic messages quickly for suicide prevention.
Advantages of ML :
So the main advantages of implementing machine learning in the social media revolution are:
- Better visual experience
Twitter has used ML to automatically sharpen the images and videos thereby enhancing the visual experience of the users. More than 80% of Twitter users see images and watch videos so live streaming is very crucial for the existing and upcoming users.
- Helps in marketing products for the target audience
The Facebook network is able to determine the topics that grab the user’s attention. It also detects spam content and also recommends the prospective content to the users.
- Data security
Pinterest uses ML technology to filter out spam content. It also predicts the likes of individual users and recommends them the content of their choice to pin.
- Data automation
Pinterest has used the ML technique to automatically attach relevant tags as the user starts entering tags. So the users need not to manually enter tags which provide the better user experience.
Conclusion:
Machine learning focuses on developing computer programs for computers to automatically learn the required things without human involvement. Machine learning technology has revolutionized the social media platform. It helps software applications to become precise in predicting outcomes, allows them to access big data and comes with powerful data analytics capabilities. The future of ML is very bright.
Author Bio
Poonam Agarwal, an experienced content writer at TechIngenious – A Mobile app development company. I am writing from the past 3 years. I love to express my views through writing. I am a day to day writer and an athlete when I am not writing.
