Udemy

Platform

English

Language

Data Science

Category

Artificial Intelligence and IoT: Naive Bayes

A project-based course to build an AIoT system from theory to prototype

4.40 (26 reviews)

7093

Students

1.5 hours

Content

Feb 2021

Last Update
$94.99
Regular Price


What you will learn

Naive Bayes classifier examples by hand

Implement Naive Bayes classifier from scratch in Python and C

Implement Naive Bayes classifier on microcontrollers

Build an AIoT system based on Naive Bayes classifier and Arduino


Description

Sample codes are provided for every project in this course.

You will receive a certificate of completion when finishing this course.

There is also Udemy 30 Day Money Back Guarantee, if you are not satisfied with this course.


This course teaches you how to build an AIoT system from theory to prototype particularly using Naive Bayes algorithm. This course is divided into three main parts. In the first part, you will learn about Naive Bayes classifier examples by hand. In the second part, you will learn about how to implement Naive Bayes classifier from scratch in Python and C. In the third part, you will learn about how to build an AIoT system based on Naive Bayes classifier and Arduino.

This is a project-based course. The main goal is to show you the complete flow how to build AIoT from theory to prototype. The point is to apply the concepts that you will learn in this course to your own projects. At the end of this course, you will be able to combine various kinds of knowledge that you may have studied at university, such as Artificial Intelligence, Programming, and Embedded System, in order to build the complete prototypes.

So, click the course button and see you inside the course.


Screenshots

Artificial Intelligence and IoT: Naive Bayes
Artificial Intelligence and IoT: Naive Bayes
Artificial Intelligence and IoT: Naive Bayes
Artificial Intelligence and IoT: Naive Bayes

Content

Introduction

Prologue

Required Components

Source Code

=== Part 1: Theory

Welcome to Part 1: Theory

Naive Bayes Classifier by Hand (One Input Feature)

What is Naive Bayes?

Conditional Probability

Naive Bayes Example 1

Naive Bayes with One Input Feature (by Hand)

The Naive Bayes Formula

Laplace Smoothing

Summary

Naive Bayes Classifier by Hand (Multiple Input Features)

Naive Bayes Example 2

Naive Bayes with Multiple Input Feature (by Hand)

The Naive Bayes Classifier Formula (Updated)

Summary

=== Part 2: Modelling

Welcome to Part 2: Modelling

AI Light Bulb Modelling by Hand

AI Light Bulb

Training Data

Build the Model

AI Light Bulb (by Hand)

AI Light Bulb Modelling in Python

Required Programming Tools

Data Preprocessing

Create Frequency Tables

The Solution to the Quiz (Create Frequency Tables)

Calculate Prior Probability

Calculate Likelihood

Calculate Posterior Probability

Summary

AI Light Bulb Modelling in C

Required Programming Tools

Overview of Naive Bayes in C

Naive Bayes Functions in C

=== Part 3: Prototyping

Welcome to Part 3: Prototyping

AI Light Bulb Prototyping in Arduino ESP32: Serial I/O, Sensors, LED

Required Programming Tools

AI Light Bulb with Serial Monitor I/O

LED

BH1750 Light Sensor

DS1307 Real-Time Clock

SSD1306 OLED Display

AI Light Bulb with LED, Light Sensor, and Real-Time Clock

AI Light Bulb Prototyping in Arduino ESP32: Wi-Fi, Telegram Bot

Create a New Telegram Bot

Wi-Fi and Telegram Bot

Control an LED using Telegram Bot

AI Light Bulb with Telegram Bot

Summary

Summary of the Course




Coupons

StatusDateDiscount
Expired2/14/2021100% OFF

3452488

Udemy ID

8/27/2020

Course created date

2/14/2021

Course Indexed date
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