Technology is getting smarter day by day and that various systems are being developed to generate automatic statistical techniques. This is essential for making clever real-time decisions. One such technology that has been incorporated into the field of computer science is “Machine learning.’’ Don’t get it mistaken for Artificial intelligence, it’s a totally different branch of technology. Then what machine learning exactly is? Let’s explore this amazing learning behavior of technology.
What is Machine Learning?
By definition, machine learning ‘is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.’’ It is a technology that enables a computer system to take actions using historical data.
Due to its ability to automatically learn from experience just like humans, it has gained prominent recognition worldwide. Machine learning is based on algorithms that rely on a predetermined equation as a model and equips computational methods to learn information from data directly.
To put it out in simple words, the technology’s performance improves with an increase in the number of samples available for learning. Learning from previous computations and transactions, these applications produce reliable and informed results.
Related | What is Artificial Intelligence with Examples
Types of Machine Learning
Machine Learning is basically divided into three types:
1) Supervised Learning
Considered to be the most important paradigm and the easiest to incorporate in machine learning, supervised learning is the ability to train a machine using data using labels. Basically, the system is introduced to various example-label pairs and the algorithm predicts the example for the same.
The algorithm eventually learns from labeled training data and helps you predict outcomes. It also comes with the ability to solve various types of real-world computation problems. Some of its popular applications include advertisement popularity, spam classification, and face recognition.
2) Unsupervised Learning
Unsupervised learning differs from supervised learning in that it does not require labels to understand the properties of data. Here, the system will be provided with all the data and asked to discover its own information. These algorithms let you perform more complex processing tasks and help find all kinds of unknown patterns in data.
Compared to labeled data, it’s far easier to obtain unlabeled data from a computer and thus is an important branch of machine learning. You can use unsupervised learning in areas such as recommender systems, buying habits, grouping user logs among many others.
3) Reinforcement Learning
Reinforcement Learning is an important area of machine learning that is set to find the best possible behavior the algorithm should take in order to render an outcome for a specific situation. In this type of learning, the reinforcement agent is responsible to perform the given task and as all this happens in the absence of a training dataset, the algorithm automatically learns from its experience.
In the real world, you can find Reinforcement Learning in video games, industrial simulation, resource management, and various others.
Where is it used?
Knowing what a great technology machine learning is, you might also want to know where it is used in the real world. Machine learning’s application lies in various segments, let’s take a look at the same.
Voice search on google is a category that falls under speech recognition and is something that involves the use of machine learning. It helps convert the voice instructions to text.
Prediction of traffic
One of the most significant applications of machine learning is that it is capable of predicting traffic conditions. For instance, while using google map for location information, it suggests you the current traffic at that particular location. This too uses the algorithm of machine learning.
Image Recognition, one of the most advanced search options, also relies on machine learning algorithms. The technology is used to identify various objects.
Healthcare utilizes machine learning in wearable sensors that provides information about a patient in real-time including heartbeat, blood pressure, and overall health condition. Healthcare workers can analyze the condition of the patient and predict the medications for an accurate diagnosis.
I am sure you may have got a lot of spam emails in your inbox but have you ever wondered what categorizes it into spam. It’s nothing but the algorithm of machine learning behind it. Multi-Layer Perceptron, Decision tree, and Naïve Bayes classifier are some of the machine learning algorithms that are used to detect spam emails.
Personal Assistant (Virtual)
Google Assistant, Alexa, Cortana, Siri are some of the most popular virtual assistants that we have on our devices. As we instruct the assistant, it records the information and sends it to the server which is later analyzed by a machine learning algorithm.
The transactions that we make online are secured by machine learning technology. How? Whenever you make a transaction through an online gateway, there are chances for fraud to occur. In order to prevent this, the Feed Forward Neural network acts as a carrier and makes sure whether the transaction is fraud or not.
Marketing and Sales
The product recommendations that you get are based on nothing but machine learning technology. The Marketing and Sales agencies analyze your purchase history and suggest personalized products based on your data.
What is the best programming language for machine learning?
Python is the best programming language for machine learning
What are the types of machine learning?
Supervised learning, Unsupervised Learning, and Reinforcement learning are the three types of machine learning
Does Tesla use machine learning?
Yes, Tesla has been said to incorporate machine learning for the creation of innovative neural networks all across the globe.
Are machine learning jobs in demand?
Yes, machine learning jobs are extremely high in demand.
So this was all about what is machine learning and where it is used, I hope you have understood the aspects related to machine learning. Incorporating this algorithm into various systems will let it perform complex tasks without any human intervention. All in all, machine learning is an exciting field of technology and will upload a great scope in the future.
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