Machine Learning Algorithms
To know about these Machine learning algorithms and for understanding these algorithms we firstly must know What is machine learning? and What is the Machine learning language?
Machine Learning algorithms can be developed using any of the coding and programming languages like Python, C language, C++ language.
Machine Learning algorithms can be developed using any of the coding and programming languages like Python, C language, C++ language.
What are Machine learning Algorithms?
Machine learning algorithms are programs that can learn from the data and do improvement in the experience without any interference of humans.These algorithms are developed for the better performance of the program. It is a program with a way with which you can adjust the parameters according to your choices. Machine learning is very important to learn nowadays as it helps in the saving of your time during the development of the programs and also enhances the performance of it.
- Types of Machine learning algorithms
Machine learning algorithms are of three types and these are:
- Supervised learning
- Unsupervised learning
- Reinforcement learning
* Supervised learning
It is further divided into two types that is classification and Regression. This type of learning helps in the label training data to learn the mapping function.
- Classification-When the output variable in the form of categories it helps to predict the outcome of the given sample.
- Regression- When the output variable in the form of real value it helps to predict the outcome of the given sample.
*Unsupervised learning
This is used when we only do not have any corresponding variables and have only the input variables. There is the use of the unlabeled training data to learn the mapping function.
There are Three types of Unsupervised learning algorithms: Clustering, Association, Dimensionality Reduction.
- Clustering- Helps in a grouping of the samples.
- Association- It is used to discover the probability of the Collections co-occurrence.
- Dimensionality Reduction- Used to reduce the number of variables of data.
*Reinforcement
It is a machine learning algorithm that allows agents to take the decision for the better next actions by learning the behavior based on its current state that will increase the reward.
- Classification-When the output variable in the form of categories it helps to predict the outcome of the given sample.
- Regression- When the output variable in the form of real value it helps to predict the outcome of the given sample.
*Unsupervised learning
This is used when we only do not have any corresponding variables and have only the input variables. There is the use of the unlabeled training data to learn the mapping function.
- Clustering- Helps in a grouping of the samples.
- Association- It is used to discover the probability of the Collections co-occurrence.
- Dimensionality Reduction- Used to reduce the number of variables of data.
It is a machine learning algorithm that allows agents to take the decision for the better next actions by learning the behavior based on its current state that will increase the reward.
Machine learning used for the better performance of the programs.
Machine learning is the basic requirement for the coders and programmers these days to code and develops software and applications.
To translate the human's language into computer language we need to know the basics of machine learning.
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