Last Updated on November 6, 2020
Machine learning is the subset of Artificial intelligence, it gives systems the ability to learn and improve itself through the experience without being programmed. It uses statistics to find the pattern in a large amount of data and that data can be a lot of things like numbers, images, words, or anything you have. If it can be digitally stored, it can be fed into a machine learning algorithm.
To train the system, it needs a large amount of data. If you think you will train your system using 100-200 data (such as images), still it will provide output but with less accuracy.
To get more accuracy, you have to train it with a huge amount of data. If you are thinking, where to get that massive amount of data and required resources, you can check it out Kaggle. is an online community of machine learning learners.
It is full of algorithms that solve different problems in the field of healthcare, defense, banking, comprehensive analysis, forecast, etc. Even now we can’t predict what machine learning will do in the future. Every giant companies and startups are using AIML to predict the market. Whether a person wants to become a data scientist, data analyst, AI engineer, or ML engineer, it is mandatory for them to learn machine learning.
On the basis of how the model learn and solve problems, Machine Learning is categorized into four parts:-
Applications of Machine learning
There are various machine learning applications we are using in day to day life. Some of them, you might know. If not, read below.
1. Image recognition
Image recognition is one of the most commonly used applications. It is used to recognize objects, peoples, places, etc. In smartphones, face recognition is used to unlock the phone. A Spanish bank Caixa bank becomes the first bank to implement facial recognition to their ATMs which authenticate the people, enabling them to withdraw money without having a card or PIN.
Facebook uses auto-friend tagging suggestions. Whenever we upload a photo with our friends, it automatically detects them and gives a suggestion with the name. The technology behind this face detection used by Facebook is ‘Deep face’.
2. Speech recognition
It is available on every smartphone or computer. When we go to the browser to search something, there is a type of icon on the right side of the search bar i.e. search by voice.
Nowadays many devices and gadgets are available in the market such as Siri, Alexa, Google assistant which recognizes the voice and performs by the commands.
3. Traffic prediction
When you have to go somewhere(unknown place), you use Google maps, you see the path with the shortest route and colored as per traffic condition. Here Google uses a machine-learning algorithm to present it.
4. Product recommendation
Various eCommerce companies and websites use Machine Learning. Suppose you search for earphones on Amazon but didn’t buy it. After some time you noticed while surfing the browser, you get the advertisement for those products on the screen.
Did you know how this happened? This is Machine learning !!. Those companies know the user’s interest, based on surfing or shopping then recommend them the desired product.
5. Self-driving car
If anyone heard about AI or ML, the first thing came to mind i.e ‘Self-driving car’. This driverless car is fully automatic. There is no need for the driver to operate. Tesla, the most popular automobile company is working on self-driving cars. It is using an unsupervised learning method to train the car to detect people and object while driving.
6. Stock market trading
In the stock market, there are always ups and downs in shares, here ML algorithm LSTM(Long short-term memory) helps to predict its trends.
7. Automatic language translation
If we go to some new place and we don’t know the language there, we take out Google’s GNMT(Google neural machine translation)help, which translates the text into our language. GNMT is part of machine learning.
8. Online fraud
Whenever you do some online transactions, there may be a chance of fraudulent transactions such as fake ids, fake accounts, and a steal of money in mid of the transaction. To detect this, the ML algorithm Feed-Forward neural network helps us by clicking where it is genuine in fraud transactions. So that you can save your money.
Every year,1000-2000 online fraud cases registered in India. Now many companies are using Machine Learning for protection against fraud. Paypal uses ML for protection against money laundering.
Nowadays, a number of websites offer the option to chat with a customer support representative within the site. But on some websites, you talk to a chatbot(chat + robot). What chatbot do, they extract information related to the contents of the website. By the time, it improves its service and serves better. Here it is possible due to Machine learning.
I hope you like the article.
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