Once you have successfully built a machine learning model, one of the first challenges is putting the model into production so that it can be used for realistic purposes. One of the best ways to achieve this is to create a REST API for your model so that the model can ...

Designing a neural network means creating the right architecture to achieve optimum results. This optimum, more than often, is 'vague' as this depends on the balance of model performance and computational expenses required to train the model and predict. However, even with this loosely defined term 'optimum', to begin with ...

To demonstrate the automated feature selection methods in Python we would use the diabetes dataset. Import the diabetes .csv file into a data-frame with Pandas as below:  

import pandas as pd
names = ['preg', 'plas', 'pres', 'skin', 'test', 'mass', 'pedi', 'age', 'class']
df_diabetes = pd.read_csv('diabetes.csv', names = names)
df_diabetes ...