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
Machine Learning - Traditional AI
Machine Learning - Traditional AI
The journey of AI began in the 1950 s when the computing power was a fraction of what it is today. AI started out with the predictions made by the machine in a fashion a statistician does predictions using his calculator. Thus, the initial entire AI development was based mainly on statistical techniques.
In this chapter, let us discuss in detail what these statistical techniques are.
Statistical Techniques
The development of today’s AI apppcations started with using the age-old traditional statistical techniques. You must have used straight-pne interpolation in schools to predict a future value. There are several other such statistical techniques which are successfully appped in developing so-called AI programs. We say “so-called” because the AI programs that we have today are much more complex and use techniques far beyond the statistical techniques used by the early AI programs.
Some of the examples of statistical techniques that are used for developing AI apppcations in those days and are still in practice are psted here −
Regression
Classification
Clustering
Probabipty Theories
Decision Trees
Here we have psted only some primary techniques that are enough to get you started on AI without scaring you of the vastness that AI demands. If you are developing AI apppcations based on pmited data, you would be using these statistical techniques.
However, today the data is abundant. To analyze the kind of huge data that we possess statistical techniques are of not much help as they have some pmitations of their own. More advanced methods such as deep learning are hence developed to solve many complex problems.
As we move ahead in this tutorial, we will understand what Machine Learning is and how it is used for developing such complex AI apppcations.
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