In today world you can’t be escaped the headlines, reports, whitepapers and even television coverage on the rise of Big data, Data Science and Machine Learning.Machine learning is actively being used today, perhaps in many more places than one would expect. Now coming to the point what is Machine Learning there are lots of definitions given by lots of people but according to Arthur Samuel(1959) :” computers the ability to learn without being explicitly programmed” but Tom Mitchell (1998) Well-posed Learning Problem: A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.
What is machine learning?
In the simple word you can say that “Machine learning is a technique to teach programs that use data, to generate algorithms instead of explicitly programming an algorithm from scratch.”
Machine Learning is a field of computer science which originates from the research in Artificial Intelligence so we can say that it is the subfield of Artificial Intelligence.
Applications Area of Machine Learning
- Web Search Engine: Have you ever think that how Google or other search engine works? How they show you an appropriate result or they index the web pages and other many more stuff which is very complex to solve in a normal way. These all are possible due to There are different types of complex learning algorithm uses in a search engine.
- Spam Detectors: Our mail agents like Gmail, Hotmail or others do a lot of hard work to classify the mail as spam or not spam.
- Image Tagging Application: Be it Facebook or any other photo tagging application, the ability to tag friends makes it even more happening. It is all possible because of a face recognition algorithm that runs behind the application.
- Language Translation: We all know Google Translate, the website that can instantly translate between 100 different human languages as if by magic. It is even available on our phones and smartwatches.
- Understanding Human Learning: This is the closest we have understood and mimicked the human brain. It is the start of a new revolution, The real AI. Now, After a brief insight lets come to a more formal definition of Machine Learning. read article1 and article2.
Companies using Machine Learning to improve business decision, increase productivity,detect fraud,weather forecasting, chat boats etc. and it is certainly true that there will lot of field where machine learning will stands either it would be data related or hardware related field because deep learning is on the way and it can be used with IOT(Internet Of Things).
Types of Machine Learning
Supervised Learning: The computer is presented with a given set of inputs and their respective outputs. The goal of the program is to learn from the inputs in order to reproduce the outputs.Examples of algorithms are (A)Linear Regression (B) Logistics regression (C) Decision Tree (D) The naive Bayes classifier etc.
Unsupervised Learning: There is no target variable in the case of unsupervised learning. The computer is left on its own to find patterns within the data. Example of algorithms are: (A)The k-means clustering (B) Hierarchical clustering Reinforcement Learning: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent). The program is provided feedback in terms of rewards and punishments as it navigates its problem space.
In this article, we saw the basic concept of machine learning.
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