Regression Models
Dive into a Keras' regression model and describe each step that went into developing it.
We'll cover the following...
The Predict Hourly Wage dataset is taken from Kaggle. Make a model to predict wages per hour. The dataset contains the following columns:
Read and explore the data
Read the data from the given hourly_wages_data.csv
and check for any missing values.
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main.py
hourly_wages_data.csv
import pandas as pdimport keras# read in data using pandastrain_df = pd.read_csv('hourly_wages_data.csv')print("Training data:\n", train_df.head())# sum the missing values in each columnnull_values = train_df.isnull().sum()print("Checking for null values:\n", null_values)
Line - 4: Reads the data in train_df
using the read_csv
method.
train_df =
...