Machine learning is quite an exciting field to study and rightly so. It is all around us in this modern world. From Facebook’s feed to Google Maps for navigation, machine learning finds its application in almost every aspect of our lives. It is quite frightening and interesting to think of how our lives would have been without the use of machine learning. That is why it becomes quite important to understand what is machine learning, its applications and importance.
Machine learning is quite an exciting field to study and rightly so. It is all around us in this modern world. From Facebook’s feed to Google Maps for navigation, machine learning finds its application in almost every aspect of our lives.
It is quite frightening and interesting to think of how our lives would have been without the use of machine learning. That is why it becomes quite important to understand what is machine learning, its applications and importance.
To help you understand this topic I will give answers to some relevant questions about machine learning.
But before we answer these questions, it is important to first know about the history of machine learning.
You might think that machine learning is a relatively new topic, but no, the concept of machine learning came into the picture in 1950, when Alan Turing (Yes, the one from Imitation Game) published a paper answering the question “Can machines think?”.
In 1957, Frank Rosenblatt designed the first neural network for computers, which is now commonly called the Perceptron Model.
In 1959, Bernard Widrow and Marcian Hoff created two neural network models called Adeline, that could detect binary patterns and Madeline, that could eliminate echo on phone lines.
In 1967, the Nearest Neighbor Algorithm was written that allowed computers to use very basic pattern recognition.
Gerald DeJonge in 1981 introduced the concept of explanation-based learning, in which a computer analyses data and creates a general rule to discard unimportant information.
During the 1990s, work on machine learning shifted from a knowledge-driven approach to a more data-driven approach. During this period, scientists began creating programs for computers to analyse large amounts of data and draw conclusions or “learn” from the results. Which finally overtime after several developments formulated into the modern age of machine learning.
Now that we know about the origin and history of ml, let us start by answering a simple question - What is Machine Learning?
You got intrigued by the machine learning world and wanted to get started as soon as possible, read all the articles, watched all the videos, but still isn’t sure about where to start, welcome to the club.
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