Use case implementation using tensorflow

Using cansus data, let's use several traits of an individual to estimate what income class they belong to (>50k or <=50k).

here with cansus data's drive link.

https://drive.google.com/drive/folders/1NPPMs52EOkPUTwimmyCBx0b7qCeQ-9yB?usp=sharing


Q1) what is the advantage of using TensorFlow?

the main advantage is  TensorFlow offers high-level APIs. In this case we will use estimator API to create Classifier (linearClassifier).


in census_data .csv keep age, workclass, Final-weight, education,education-num,Marital-Status,occupation,relationship,race,sex,capital-Gain,Capital-loss,hours-per-week,native-country,class coloums.here  class coloum is our target 

let's build a model

read the census_data.csv using the pandas library.

import pandas as pd
census = pd.read_csv("/content/census_data.csv")

cheak and view  census_data.csv head/1st row ,using head() function.

census.head()





more...

My_income-class-prediction-using-tensorflow.ipynb👇👇

https://colab.research.google.com/drive/1UMpS75q2CHknMFvNdTzF6J2CfeHgwK4I?usp=sharing


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