
Scikit learn library
"Once you get stick to it,
you will be lost in it"
1. Linear Regression

Simple Linear Regression

Multiple Linear Regression
2. Logistic Regression
3. KNearest Neighbor
4. KMeans Clustering
This includes among the most essential libraries to make our programs shorter. ScikitLearn is prominent for installing ML models of linear regression, logistic regression, etc. It provides input datasets for easy access. It helps to split data into a single statement.

NumPy
It is an integrable part of developing integral parts of ML. It allows us to create Ndimensional array objects, perform linear algebra, and much more. Most deep learning libraries use NumPy as their model datatype for tensors.

Matplotlib
It is a visualization library used to display your training data or your output data. This library is in competition with Seaborn, but I personally prefer Matplotlib due to experiences.

Pandas
It is a manipulation of data and analysis of the library. It is commonly used to create a specific data structure called DataFrame out of CSV/excel files. We can access data through it.
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