“There was a little girl, Liza. She used to live on a farm and had no friends in her neighborhood. On her birthday, her parents gave her a robot as a gift. She wanted the robot to be her companion, play games, solve puzzles, and dance with her. She tried hard to incorporate the robot into her activities but failed. That is until she discovers machine learning, a superpower that enables robots to learn and perform tasks on their own.
Liza began researching machine learning and taught her robot using the supervised learning method. After demonstrating numerous examples of what she wants it to do, the robot started following her instructions and can now play games, solve puzzles, and even dance better than Liza! She realizes that machine learning is a superpower that can improve and simplify things for both her and her robots.
With machine learning, computers and robots can learn from examples and make decisions on their own.”
What is Machine Learning?
Machine learning is a way for computers and robots to learn things on their own, like playing games or solving puzzles. It’s a subfield of Artificial Intelligence, and it’s becoming really important for people’s careers.
That means if you learn about machine learning, you could have a really cool job in the future! It is one of the fastest-growing, high-demand emerging skill sets.
Recommended Reading: AI for Kids: What You Need to Know
Do you know what makes Machine Learning fascinating?
Its ability to copy human behavior. It predicts outcomes without being explicitly programmed to perform the tasks, and the software applications help them in accomplishing the task.
How does machine learning work?
Data is the backbone of Machine Learning. Machines learn from the vast data/information stored in them. It allows computers and machines to access data (information), extract information from the data, learn from past mistakes without any human intervention, and give accurate results.
Machine learning can program, type in or speak a command using the data.
Interestingly, Machine learning algorithms use past data as input to predict new output values. However, Machine learning has a limited scope as they can perform only specific tasks they are trained for.
Now let us talk about types of Machine Learning. There are three types of ML –
1) Supervised Learning
In this, the machine is given both input and out parameters, and the machine uses the information.
2) Unsupervised Learning
In this process, a large amount of data is fed into the and asked to find patterns and relationships on its own, without any specific answers.
Reinforcement Learning: When the computer makes a decision based on the feedback it receives on its action or behavior, it is called reinforced learning.
AI vs Machine Learning
Let us first understand the difference between AI and Machine Learning.
AI makes it possible for machines to act like people, and Machine Learning helps those machines learn and improve on their own without being specifically told what to do. Just like when you. When you grow older, you become independent and make your decisions without depending on your parents.
Applications of Machine Learning
1) Traffic Alerts: Nowadays, everyone uses Google Maps, and the alerts about traffic congestion or free route that you receive during the drive are the best example of machine learning. Google stores the traffic data of the route, which enables it to predict upcoming traffic and suggest routes accordingly.
2) Alexa: Amazon’s natural language processing system is another example of machine learning. Data and machine learning are the base of Alexa. You may not have paid attention to Alexa’s behavior, but next time when you use it you must notice that every time it makes a mistake in interpreting your command, that data is used to make the system smarter the next time around. Machine learning fuels the constant improvement in the capabilities of the voice-activated user interface.
3) Uber: Uber, a personalized application, has seen a phenomenal rise. The app automatically detects your location and uses your history and patterns to provide options to either go home or office, or any other frequently visited destination.
4) Product Recommendations: You must have experienced this. You do a survey on Amazon for a bicycle of a particular brand, but you do not buy it. Next time when you are browsing the net or checking your Facebook page, you see an ad for the same item. Do ever wonder how it happens? Simple. Google tracks your search history and recommends ads based on that.
5) Music or video recommendations: If you spend time on YouTube, you must be getting recommendations based on your taste and preferences. How does it know which video you may like? Machine learning makes it possible. It uses your history and processes the information to filter out the recommendation for you.
So, next time you get a traffic alert or a recommendation from YouTube, you know it’s all because of Machine Learning.
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