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Scikit learn library
"Once you get stick to it,
you will be lost in it"
1. Linear Regression
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Simple Linear Regression
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Multiple Linear Regression
2. Logistic Regression
3. K-Nearest Neighbor
4. K-Means Clustering
This includes among the most essential libraries to make our programs shorter. Scikit-Learn 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.
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NumPy
It is an integrable part of developing integral parts of ML. It allows us to create N-dimensional array objects, perform linear algebra, and much more. Most deep learning libraries use NumPy as their model datatype for tensors.
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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.
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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.
Some popular sayings
Blogging
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