If you belong to technology lovers gang, you might have already heard of Machine Learning(ML) and Machine Learning Algorithms.
What are machine learning and machine learning algorithms?
Formally, Machine Learning is a sub-part of Artifical Intelligence. It is an important part of artificial intelligence. Now coming to definition, according to N. Mitchell
“A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.”
Now coming to direct meaning of it, here in machine learning algorithms, such algorithms are made which can improve their output every time with experience/data passed through algorithm or model.
What makes Machine Learning Algorithms Different?
In normal cases, we provide some input to get some output from the program, but in case of machine learning algorithms, we provide input to get some desired output expecting that algorithm will improve output with next iteration/pass.
Different Types Of Machine Learning Algorithms:
Machine Learning can be classified on the basis of learning algorithms.
General types of machine learning:
- Supervised Learning.
- Unsupervised Learning.
- Reinforcement Learning.
In supervised learning we provide X-Y(called as pre-classified examples) to model, now on the basis of observation find the most appropriate Y’ corresponding to new input X’. Where X is set of input features and Y is target feature.
Further supervised can be classified into two parts:
A) Classification: Where Y is discrete.
B) Regression: Where Y is continuous.
In unsupervised learning, we make the cluster/group on basis of features of X(input).
Determine what to do based on rewards and punishments.
Currently, ML is a demanding field every day something new is added to it. Artifical intelligence and big data are helping in the growth of Machine learning. Soon, it will surpass many big innovations and technology.