Machine Learning is made of two words-“Machine” + “Learning”. The whole subject of training a machine which means a computer system to solve problems in day to day life to enable better decision making through accurate predictions and forecasts is called Machine Learning.
Machine Learning is an amalgamation of the field of statistics, mathematics, computing and artificial intelligence. Though this may sound as a complex subject for a layman with non technical background, the area is vast and interesting and has vast usage in day to day life. A simple example is weather forecast where historical or seasonal weather data is analyzed to make weather forecasts. Another example is analyzing historical sales data to predict product sales for next 6 months. Another example is analyzing traffic data in real time to predict the traffic conditions on connecting routes in real time and giving alerts to users based on that to avoid further congestion.
Applications such as these not only make this topic interesting but also as newer areas get added to the ambit of Machine Learning, there is a wide scope to further refine different algorithms on which machine learning is based.
The succeeding pages give the reader with non technical background a peek into “What Machine Learning actually is”, “Different steps that are present in Machine Learning process”, “Application of Machine Learning” and “Data types in Machine Learning”.
The aim of this article is to introduce a layman to the vast field of machine learning.
Machine Learning is an amalgamation of the field of statistics, mathematics, computing and artificial intelligence. Though this may sound as a complex subject for a layman with non technical background, the area is vast and interesting and has vast usage in day to day life. A simple example is weather forecast where historical or seasonal weather data is analyzed to make weather forecasts. Another example is analyzing historical sales data to predict product sales for next 6 months. Another example is analyzing traffic data in real time to predict the traffic conditions on connecting routes in real time and giving alerts to users based on that to avoid further congestion.
Applications such as these not only make this topic interesting but also as newer areas get added to the ambit of Machine Learning, there is a wide scope to further refine different algorithms on which machine learning is based.
The succeeding pages give the reader with non technical background a peek into “What Machine Learning actually is”, “Different steps that are present in Machine Learning process”, “Application of Machine Learning” and “Data types in Machine Learning”.
The aim of this article is to introduce a layman to the vast field of machine learning.
Category
📚
Learning