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Python Top Libraries You Need to Create ML Model

Creating a Model of Machine Learning in Python, you need two libraries. One is 'NUMPY' and the other one is 'PANDA'.


For this project, we are using Python Libraries to Create a Model.
What Are Key Libraries You Need I have explained in the below steps. You need Two.
NUMPY - It has the capabilities of CalculationsPANDA - It has the capabilities of Data processing. To Build a model of Machine learning you need the right kind of data. So, to use data for your project, the Data should be refined. Else, it will not give accurate results. Data AnalysisData Pre-processing How to Import Libraries in Pythonimportnumpy as np # linear algebra
importpandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

How to Check NUMPY/Pandas installed After '.' you need to give double underscore on both the sides of version. 
How Many Types of Data You Need You need two types of data. One is data to build a model and the other one is data you need to test the model. Data to build…

Python Top Libraries You Need to Create ML Model

Creating a Model of Machine Learning in Python, you need two libraries. One is 'NUMPY' and the other one is 'PANDA'.
ML model in python


For this project, we are using Python Libraries to Create a Model.

What Are Key Libraries You Need

I have explained in the below steps. You need Two.
  • NUMPY - It has the capabilities of Calculations
  • PANDA - It has the capabilities of Data processing.
To Build a model of Machine learning you need the right kind of data. So, to use data for your project, the Data should be refined. Else, it will not give accurate results.
  1. Data Analysis
  2. Data Pre-processing

How to Import Libraries in Python

import numpy as np # linear algebra
import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

How to Check NUMPY/Pandas installed

After '.' you need to give double underscore on both the sides of version. 
how to check numpy or pandas version

How Many Types of Data You Need

You need two types of data. One is data to build a model and the other one is data you need to test the model.
  1. Data to build Model
  2. Test data to evaluate the Model

Sample Data To Build Model

I have given a flow chart to build a model along with sample data.

References
  1. Sample ML Model Project using Python

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