Machine learning has brought about a revolution, tempting the masses to conjure up visions of futuristic self-learning AI and robots. Machine learning is a set of techniques and tools that help computers learn and adapt on their own. It powers breakthrough innovations, such as prediction engines to online TV live streaming that supports our modern lifestyles. The real-life applications of machine learning are far and wide. This article concentrates on 5 such machine learning applications.
Machine Learning Applications
Social Media Services
Social media applications have long since been using machine learning algorithms and approaches to develop several extravagant and excellent features. These platforms utilize machine learning for various instances, such as personalizing your news feed to better ad targeting. Facebook, for example, continuously notices the friends that you connect with, the profiles that you visit very often, your interests etc. Based on this foundation, a list of Facebook users is suggested that you can become friends with.
One of the most popular machine learning applications is product recommendation. This is one feature that has massively helped in the growth of e-commerce as an industry by refining the entire shopping experience. Using ML and AI, websites track your behavior based on your previous purchase and various other factors and then make product recommendations.
Image recognition, which helps in cataloging and detecting a feature or an object in the digital image is one of the most important machine learning applications. The implications of this feature can be witnessed in our everyday lives. From unlocking your phone by just looking at it to self-driving cars and military surveillance, image recognition powered by ML algorithms and AI has changed the digital world forever.
Sentiment analysis is an application of machine learning that determines the emotion or opinion of the speaker or the writer. Using the model of sentiment analysis, machines equip themselves to be capable to analyze sentiments based on the words. They can recognize if the words are said in a positive, negative, or neutral notion and they can even define the magnitude of these words.
Email Spam Filtering
There are several ways email clients tackle spam mail. To ensure the proper working of these approaches, machine learning is used. ML powers these spam filters and makes sure that they are constantly updated. Multi-Layer Perceptron and C 4.5 Decision Tree Induction are some of the spam filtering techniques that are powered by ML.
Machine learning has integrated itself into our everyday lives and has constantly proven itself to be indispensable in supporting our digital lifestyles. The above mentioned are but a few of the machine learning applications that we see in our daily lives. Machine learning is also a crucial skill that young data science professionals must master to ensure a prosperous career in the same. Praxis understands this and has developed a state of the art PGP in Data Science. This program will train you in all aspects of data science and equip you with the tools needed to go out and make your mark in the professional world. Our outstanding placement records and amazing tie-ups will ensure that you get all the exposure you need to kickstart your career on a high note.
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