Trending Use-Cases of Machine Learning Algorithms!

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Machine learning uses computer algorithms that perform specific tasks automatically and without the help of a human. Machine learning algorithms build a statistical model by taking sample data. The global revolution of advanced technology brings heavy-loaded computational power, advanced with machine learning. Machine learning is worth to be one of the most successful and large-spread technology in today’s world, evolving from artificial intelligence research. As a sub concern of artificial intelligence, machine learning widely opens up ways for making such huge impacts on the business and every other sector with futuristic technology. It’s time to deep down discussing some use cases of machine learning on board.

Smart Assistants

Suppose you need some customized reminders while you involve deeply at work, or you want to control your home devices. Things have changed from appearing the Siri or Cortana to every type of personal assistant to date. We can’t but use these smart assistants for getting reminders, turning our light off, or maybe searching for information. These smart-assistant systems rely on machine learning for collecting every piece of information that you provide to these. By evaluating the data, these devices understand the user’s preference, choices by ML algorithms. It shows the analytical and daily basis updates from clients to improve their experience with individuals. 

Social Networking Platforms

Facebook: 

Particularly inside Facebook, there’s a vital role in artificial intelligence and the use of machine learning algorithms. You might have seen the auto-tagging when you post any picture on your Facebook wall. It detects your and other people’s faces by Artificial Neural Network(ANN). Facebook uses AI for personalizing your home feed. That’s why whatever you see on Facebook wall, is most relevant to your interest and choices. 

Snapchat: 

This platform powers by numerous facial filters and lenses that are super fun to use. It takes permission from the user to attach some artificial stickers, filters that measure faces through ML algorithms, and transforms as the faces move. 

Besides these, there’s a long list of ML-powered social media platforms such as Instagram, Pinterest, etc.

Writing Evaluation

Machine learning algorithms are equally important in building a plagiarism detector. A copy-text detector system that is known as a plagiarism detector; is more useful and less erroneous through ML algorithms. For every professional documentations, institutional requirements, your writing needs to be error-free and plagiarized-free. The algorithmic combination of plagiarism brings the numerical estimation of how close your documents in comparison to other relevant texts. More necessarily, it is suitable for the writing community to detect if you are cultivating unique write-ups or having unethical practices. 

Furthermore, an AI-powered essay grading system already exists that automatically can evaluate your essay. Popular as e-rater, where GRE examinations are also get examined through human readers as well as robot-reader. 

Email Intelligence

Electronic mails are another essential part of our professional communication. We somehow find certainly unknown, redundant, spam emails that can be a threat to us. Machine learning offers some incredible features that filter your incoming mails from many sources and signals and analyses, from where it comes from, who sent it. With the help of ML algorithms, Gmail can filter up to 99% of the spam message. 

Moreover, the categories such as promotions, primary, social, updates, etc. you see are the results of machine learning filtration.

Conclusion

If we look back to the last couple of years standing in 2020, there’s a lot of essential digital technology that has appeared. Artificial intelligence and machine learning have brought us much comfort. These allow us taking more worthy business decisions. In our personal or professional lives, the importance of optimizing operations, taking the decision, and augmenting productivity for industries is nothing but crucial. A kindful appreciation goes for machine learning that has enabled many use cases in our daily lives for the betterment indeed. 

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