Hands-On AIoT: Simple Logistic Regression

In this tutorial, you are going to learn how to deploy a simple logistic regression model. The model predicts rains based on humidity. It is modeled in Python from scratch. Then, you are going to deploy this model as a C Arduino application on ESP32. Finally, you are going to use sensor data as input to the model and display prediction using web UI that is hosted on the ESP32.

We are going to use several software technologies, such as Python, HTML, CSS (Bootstrap), and JavaScript (TensorFlow.js). On the hardware, we are going to use the WiFi of the ESP32, and DHT11 temperature and humidity sensor. At the end of this tutorial, you will be able to build the following system.

This tutorial teaches you how to build a simple logistic regression model from the scratch. This process is quite useful, rather than you just read a little bit of the theory and then start using libraries. Because you will better understand how the algorithm works. Once you understand the algorithm, it is relatively easy to use any libraries. This tutorial is divided into several parts as follows. So, let’s get started.

Contents

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