Hasn’t every single one of us, at least once, used face recognition to unlock your phone, seen a YouTube video suggestion that was suspiciously fitting or used Google translate and gotten a different perspective to a language we know nothing about?
That was the ML standing behind the scene doing its magic without anyone being aware of it.
Artificial intelligence or machine learning, therefore, is not just an advertisement headline in the technology world but rather incorporated in our lives today without us barely realizing it. In this post, let’s take a look at a list of 10 real-life examples of ML that you’ve probably encountered today!
1. Face Recognition in Smartphones
Face ID or any of the facial unlock in Android essentially illuminates the phone and identifies the facial landmarks and looks for a match with an image stored in the device. This is made possible through an ML algorithm process that uses multiple views and undergoes changes in conditions such as haircuts, glasses, or changes in lighting.
Real-World Example: Iphone face id, android facial recognition
2. Email Spam Filtering
Do you pay attention to how gmail or outlook first separates spam, promotion emails and the main inbox emails so efficiently? This is how ML works — identifying the patterns in the content of the incoming emails and user’s behavior to protect your inbox.
Real-World Example: Gmail Spam Filtering, Outollook Junk Mail Filtering
3. YouTube & Netflix Recommendations
YouTube is always on the pulse to predict what is the next video you could enjoy, isn’t it? This is due to the fact that Netflix suggests what you can watch depending on the movies that you have already watched. These applications rely on artificial intelligence whereby the programs or apps analyze your watching history, your interests, and even the duration you spend watching videos or episodes.
Real-World Example: Netflix, YouTube, Amazon Prime Video
4. In this blog, terms such as Virtual Assistants (Siri, Alexa, Google Assistant) will be used to refer a range of voice based AI-powered personal assistants.
Just say, ‘Hey Siri” or ‘Okay Google,” and your voice assistant is right there to assist you. These helpers employ the Natural Language Processing (NLP) based on some sort of Machine Learning to comprehend your sound, tone, accent, and even the need.
Real-World Example: Siri, Alexa, Google Assistant, Bixby
5. Self-Driving Cars
Self-driving cars such as the Tesla use machine learning in an effort to perceive roads through physical sensing and cameras. The system is able to identify pedestrians, traffic signals, other automobiles and begin to make certain choices as one would expect from a human driver.
Real-World Example: Tesla’s Autopilot, Waymo, and Cruise are the most popular ones being initiated by General Motors.
6. Healthcare & Disease Prediction
There are now increasing probabilities of using machine learning techniques into analyzing X-ray, CT scan, and laboratory diagnosis reports. By applying these models, one can identify the disease – be it cancer, pneumonia or COVID-19 at an earlier stage and in most cases more accurately.
Real-World Example: Artificial Intelligence (AI) applications on cancer detection, AI-based solutions in COVID-19 predictions, and AI for radiologists
7. Online Shopping Recommendations
Every time you put in one item in the cart, have you ever been offered something like it? E-commerce sites use ML to:
- Recommend products
- Predict your shopping behavior
- Set dynamic prices
Real-World Example: Amazon, Flipkart, Myntra, Shopify
8. Fraud Detection in Banking
Although some measures have been taken, such as notification when you use the card in a different city or use the card for transactions of large amounts . That can be defined as machine learning that detects an irregularity in your spending pattern to eliminate fraud.
9. Language Translation
Google Translate not only translates word for word but also uses machine learning for grammar, context, and even the structure of the sentence itself. Similarly, there are many such apps like Duolingo that let the learners have lessons that are to be suited as per the learner’s learning ability.
Real-World Example: Google Translate, Duolingo, Microsoft Translator
10. Social Media Feeds
These apps present you with content that you are likely to have an interest in viewing; this include Facebook, Instagram, twitter, tiktok and amongst others. These apps get data from the likes, shares, scrolling time, and the things that are not even clicked, to create a feed.
Real-World Example: Instagram Explore, Facebook Timeline and TikTok For You Page
Conclusion
Machine learning today is a part of our everyday life – from your smartphone to the classroom, or even a visit to the physician. It is by understanding these applications that you get the basics to discuss more complex issues such as the algorithms, models, and other topics in the subfield of deep learning.
This is just the beginning. In future posts, we will explain more about how it all works behind the scenes — and before long, you’ll be creating your own AI project!
Click to go to Machine learning Algorithms
Comments
Post a Comment