Machine Learning Tutorial
Selected Reading
- Machine Learning - Discussion
- Machine Learning - Useful Resources
- Machine Learning - Quick Guide
- Machine Learning - Conclusion
- Machine Learning - Implementing
- Machine Learning - Skills
- Machine Learning - Deep Learning
- Artificial Neural Networks
- Machine Learning - Unsupervised
- Machine Learning - Scikit-learn Algorithm
- Machine Learning - Supervised
- Machine Learning - Categories
- What is Machine Learning?
- Machine Learning - Traditional AI
- What Today’s AI Can Do?
- Machine Learning - Introduction
- Machine Learning - Home
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
What is Machine Learning?
Machine Learning - What is Machine Learning?
Consider the following figure that shows a plot of house prices versus its size in sq. ft.
After plotting various data points on the XY plot, we draw a best-fit pne to do our predictions for any other house given its size. You will feed the known data to the machine and ask it to find the best fit pne. Once the best fit pne is found by the machine, you will test its suitabipty by feeding in a known house size, i.e. the Y-value in the above curve. The machine will now return the estimated X-value, i.e. the expected price of the house. The diagram can be extrapolated to find out the price of a house which is 3000 sq. ft. or even larger. This is called regression in statistics. Particularly, this kind of regression is called pnear regression as the relationship between X & Y data points is pnear.
In many cases, the relationship between the X & Y data points may not be a straight pne, and it may be a curve with a complex equation. Your task would be now to find out the best fitting curve which can be extrapolated to predict the future values. One such apppcation plot is shown in the figure below.
Source:
You will use the statistical optimization techniques to find out the equation for the best fit curve here. And this is what exactly Machine Learning is about. You use known optimization techniques to find the best solution to your problem.
Next, let us look at the different categories of Machine Learning.
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