Top Applications of Machine Learning
Isn’t it amazing to know that we are utilizing machine learning technology in our day-to-day lives? It is an incredible part of artificial intelligence and the steering forces behind multiple companies now.
Machine learning is a powerful artificial intelligence tool, processing big data sets and decoding the billions of bits and bytes of data in real-time. It aims to increase business scalability and boost business processes for enterprises across the globe.
Initially, let us explore the machine learning types.
Types of machine learning
Supervised, Unsupervised & Reinforced are the types of machine learning. There are two types of data in machine learning, labeled and unlabeled data. A label is nothing but a recognized definition or a tag in the data that is provided to objects.
Supervised learning is the easiest method to grasp and the simplest to execute. Labeled data is used in Supervised Machine Learning to train machines to make them learn and create relationships between the inputs and outputs given.
Unsupervised learning is the reverse of supervised learning, as it is not labeled. This method does not require human support. The tools would support the algorithm to understand the data provided, and from that data can be organized.
Reinforcement learning is not similar to supervised and unsupervised learning as it is not based on labels. It has an algorithm that uses a trial-and-error method to improve and learn from new situations. Algorithms learn from itself to find the solution.
Have a look at the infographic representation of the types and algorithms of machine learning.
Applications of machine learning
Here are some of the applications of machine learning.
Online Fraud Detection
Owing to the rise in the number of transactions, the number of fraudsters has increased through fake accounts, ids, and fraud in the middle of transactions. Machine learning is proving its ability to make cyberspace a safe place as it detects monetary fraud online. There is a particular pattern for each transaction that changes for every fraud transaction, thereby detecting it and making our online transactions more stable.
Email spam detection
Machine learning has several spam filtering approaches to detect the received spam emails. For email spam filtering, many machine learning algorithms such as Deep Learning, Naive Bayes, Support Vector Machines, Neural Networks, etc. are used.
Machine learning algorithms and methods are used by social media sites to build some enticing and excellent features. Social networking companies are using machine learning to personalize the news feed and better ad targeting. Face recognition is the application of machine learning on Facebook in which the system itself verifies a person in an image to suggest tagging options. “Friend suggestion” option on Facebook is also driven by machine learning techniques.
Online Customer Support
Chatbots are the newly introduced customer support executives, who chat like a human with the customer. It helps multiple sectors to deliver highly personalized messages, operation & customer support in one turn.
Product recommendation is another amazing feature of machine learning, as it recommends the products based on your previous purchase and search history. Have you seen the advertisements of products popping up in your social media while scrolling? This is attributed to the machine learning feature utilized by google.
Cortana, Google Assistant, Siri are some examples of virtual personal assistants. Voice recognition technology is utilized in virtual personal assistants. Machine learning is an integral aspect of these personal assistants as they collect and optimize the data based on past involvement with them. This data collection is later used to make outcomes that are personalized to your needs.
With technological advancements, machine learning is evolving and changing our lives in a rapid style. As the world depends more on digital techniques now, let’s hope to utilize the maximum benefits of this incredible technology.