tensorflowSimple linear regression structure in TensorFlow with Python


Introduction

A model widely used in traditional statistics is the linear regression model. In this article, the objective is to follow the step-by-step implementation of this type of models. We are going to represent a simple linear regression structure.

For our study, we will analyze the age of the children on the x axis and the height of the children on the y axis. We will try to predict the height of the children, using their age, applying simple linear regression.[in TF finding the best W and b]

Parameters

ParameterDescription
train_Xnp array with x dimension of information
train_Ynp array with y dimension of information

Remarks

I used TensorBoard sintaxis to track the behavior of some parts of the model, cost, train and activation elements.

with tf.name_scope("") as scope:

Imports used:

import numpy as np
import tensorflow as tf

Type of application and language used:

I have used a traditional console implementation app type, developed in Python, to represent the example.


Version of TensorFlow used:

1.0.1


Conceptual academic example/reference extracted from here: