Machine learning is amongst the most significant technological developments in recent history in the domain of artificial intelligence. Constituting one of the buzzwords in modern technology, the applications of machine learning are diverse as we turn to use technologies brought to us via this inventions without knowing. The importance of machine learning and its applications are actively present-day lives ranging from email messaging, online banking, uber, social media apps, etc. which we will explore some in this article.
Applications of Machine Learning
Machine learning being a technology in which computers, software, and devices perform via cognition (very similar to the human brain), many will see it as a very far-fetched complex word but trust me, anyone who uses his phone to chat on social media, shop online, lookup for locations, etc are constantly enjoying the applications of machine learning. Some of the common ML applications are;
1. Traffic Alerts (Maps)
Whenever we want to visit a new place, we mostly make use of Google Maps, which shows us the correct path with the shortest route and predicts the traffic conditions. How does this work? Well, it’s a combination of People currently using the service, Historic Data of that route collected over time and few tricks acquired from other companies. Everyone using maps is providing their location, average speed, the route in which they are travelling which in turn helps Google collect massive Data about the traffic, which makes them predict the upcoming traffic and adjust your route according to it.
2. Image Recognition
Image recognition is one of the most common applications of machine learning. It is used to identify objects, persons, places, digital images, etc. A popular use case of image recognition and face detection is the automatic friend tagging suggestion on Facebook or any other social media platform. Facebook uses face detection and image recognition to automatically find the face of the person which matches its database and hence suggests us to tag that person based on DeepFace. Facebook’s Deep Learning project DeepFace is responsible for the recognition of faces and identifying which person is in the picture. It also provides Alt Tags (Alternative Tags) to images already uploaded on Facebook.
3. Speech Recognition
Do you remember the famous “ok Google” alert while using Google, we get an option of “Search by voice,” it comes under speech recognition, and it’s a popular application of machine learning. Speech recognition is a process of converting voice instructions into text, and it is also known as “Speech to text”, or “Computer speech recognition.” At present, machine learning algorithms are widely used by various applications of speech recognition. Google Assistant, Siri, Cortana, and Alexa are using speech recognition technology to follow the voice instructions.
4. Google Translate
One of the major challenges when travelling to a new place is the difficulty to communicate with the locals. Well, those days are gone now. Google’s GNMT(Google Neural Machine Translation) is a Neural Machine Learning that works on thousands of languages and dictionaries, uses Natural Language Processing to provide the most accurate translation of any sentence or words. Since the tone of the words also matters, it uses other techniques like POS Tagging, NER (Named Entity Recognition) and Chunking. It is one of the best and most used Applications of Machine Learning.
5. Self-Driving Cars
One of the most exciting applications of machine learning is self-driving cars. Machine learning plays a significant role in self-driving cars. Tesla, the most popular car manufacturing company works on self-driving cars. It uses unsupervised learning to train car models to detect people and objects while driving.
6. Fraud Detection
Whenever we perform some online transaction, there may be various ways that a fraudulent transaction can take place such as fake accounts, fake ids, and steal money in the middle of a transaction. So to detect this, Feed Forward Neural network helps us by checking whether it is a genuine transaction or a fraud transaction. Whenever a customer carries out a transaction – the Machine Learning model thoroughly x-rays their profile searching for suspicious patterns. For each genuine transaction, the output is converted into some hash values, and these values become the input for the next round. For each genuine transaction, there is a specific pattern which gets change for the fraud transaction hence, it detects it and makes our online transactions more secure.
7. Video Surveillance
Imagine a single person monitoring multiple video cameras! Certainly, a difficult job to do and boring as well. This is why the idea of training computers to do this job makes sense.
The video surveillance systems nowadays are powered by AI that makes it possible to detect crime before they happen. They track unusual behaviour of people like standing motionless for a long time, stumbling, or napping on benches etc. The system can thus give an alert to human attendants, which can ultimately help to avoid mishaps. And when such activities are reported and counted to be true, they help to improve the surveillance services.
8. Virtual Personal Assistant
We have various virtual personal assistants such as Google Assistant, Alexa, Cortana, Siri. They help us in finding the information using our voice instruction. These assistants can help us in various ways just by our voice instructions such as Play music, call someone, Open an email, Scheduling an appointment, etc. These assistant record our voice instructions, send it over the server on a cloud, and decode it using ML algorithms and act accordingly.
9. Medical Diagnosis
In medical science, machine learning is used for diseases diagnoses. With this, medical technology is growing very fast and able to build 3D models that can predict the exact position of lesions in the brain. For example, Watson is a renounced program developed by IBM and has been deployed in several hospitals and medical centres in recent years, where it demonstrated its aptitude for making highly accurate recommendations in the treatment of certain types of cancers.
10. Product Recommendations
You shopped for a product online a few days back and then you keep receiving emails or ads for shopping suggestions. If not this, then you might have noticed that the shopping website or the app recommends you some items that somehow matches with your taste. This an application of machine learning and here is how it works; on the basis of your behaviour with the website/app, past purchases, items liked or added to cart, brand preferences etc., the product recommendations are made.
11. Email Spam and Malware Filtering
Have you ever wondered how your incoming emails really get automatically organized into mail folders i.e inbox or spam as they stream in? The technology behind this putting important emails into the inbox folder and unimportant in the spam folder is Machine learning. Some machine learning algorithms such as Multi-Layer Perceptron, Decision tree, and Naïve Bayes classifier are used for email spam filtering and malware detection.
Artificial intelligence has come to revolutionize the world and machine learning (ML) is just making it dynamic and fascinating with its detailed and seamless functionalities. The applications of machine learning are growing every day as this article tackles just the prominent ones at the moment.