Machine Learning And Its Types

machine learning is a part of artificial intelligence that provides the capability to learn automatically and enhance from previous experiences. it can solve any problem without any help. there is the following library used such as pandas, NumPy, matplotlib, and seaborn. we use pandas library to read the dataset. dataset can be numeral and string values. matplotlib library is used to plot visualization graph and seaborn library is also used to plot visualization graph. these are few libraries that we used to perform tasks in machine learning 

Type Of Machine Learning 

There are two types of machine learning such as:-

1. supervised algorithm
2. unsupervised algorithm 

1.supervised learning

in supervised learning input and output, information is available. there we have labeled data. Labeled data means all the information is available only need to classify it and in simple words here a supervisor is available to teach everything. 

There are the following types of supervised learning algorithms such as 

1. classification

2. regression

1. classification

when we want the result in the form of true, false, and binary form then we used classification algorithms. there are the following types of algorithms such as 

1. naive Bayes
2. support vector machine 
3. k nearest neighbors

 2. Regression 

when we have a continuous value of data then we use regression algorithms such as 

1. decision tree regression
2. linear regression 
3. logistic regression

2. unsupervised learning algorithm

in unsupervised learning, input information is available but output information is not available when we have input values only then we use unsupervised learning. there are the following type of unsupervised learning algorithms such as 

1. clustering 
2. dimensionality reduction

1. clustering 

it makes a number of groups for example if in a room many students are available of B.sc and B.tech courses. and I wanted to separate them to know about the total no. of students are available in particular courses. so with the help of clustering. I can separate them into two groups. in the first group, all BSc students will be available and in the second group all BTech students will be

there are the following types of clustering algorithms such as 

1. k-means clustering 
2. hierarchical clustering 
3. mean shift 
4. k methods  

2.dimensionality reduction 

Here we reduce the dimensions for example if a particular thing is not clear from one direction so we can change that to see clear results from the direction with the use of dimensions can be of any numbers. but we only select the best dimension which is giving proper output or result in comparison of other dimensions there are the following type of dimensionality reduction algorithms such as 

1. PCA (particle component analysis)
2. LDA (linear discriminant analysis)
3. feature selection 

These algorithms perform well on overfit datasets in reduce overfitting. it selects only important variables which reduce the overfitting problem 

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