Machine learning OpenCV based IOT using Raspberry pi

Machine learning – OpenCV based IOT using Raspberry pi, available at $44.99, has an average rating of 3.65, with 45 lectures, 5 quizzes, based on 34 reviews, and has 324 subscribers.

You will learn about Supervised learning using OPEN CV Internet of things using Raspberry Pi Configuring and acquiring data from sensor(s) by interfacing with Raspberry Pi Developing voice control interface for IOT application How Supervised learning can be used in IOT applications This course is ideal for individuals who are Beginner interested to understand Machine Learning particularly Supervised Machine learning. or Interested to learn Internet of things or Those interested to know as how Supervisory machine learning can be used IOT application or Students with background in Computer Science and Electronics It is particularly useful for Beginner interested to understand Machine Learning particularly Supervised Machine learning. or Interested to learn Internet of things or Those interested to know as how Supervisory machine learning can be used IOT application or Students with background in Computer Science and Electronics.

Enroll now: Machine learning – OpenCV based IOT using Raspberry pi

Summary

Title: Machine learning – OpenCV based IOT using Raspberry pi

Price: $44.99

Average Rating: 3.65

Number of Lectures: 45

Number of Quizzes: 5

Number of Published Lectures: 45

Number of Published Quizzes: 5

Number of Curriculum Items: 50

Number of Published Curriculum Objects: 50

Original Price: ?1,199

Quality Status: approved

Status: Live

What You Will Learn

Supervised learning using OPEN CV

Internet of things using Raspberry Pi

Configuring and acquiring data from sensor(s) by interfacing with Raspberry Pi

Developing voice control interface for IOT application

How Supervised learning can be used in IOT applications

Who Should Attend

Beginner interested to understand Machine Learning particularly Supervised Machine learning.

Interested to learn Internet of things

Those interested to know as how Supervisory machine learning can be used IOT application

Students with background in Computer Science and Electronics

Target Audiences

Beginner interested to understand Machine Learning particularly Supervised Machine learning.

Interested to learn Internet of things

Those interested to know as how Supervisory machine learning can be used IOT application

Students with background in Computer Science and Electronics

You will find course in Supervised machine learning course – OPEN CV generally for computer. But, hardly you will find an integrated course which covers Internet of things? based on supervised machine learning output. In really, for machine learning in real time has no meaning when it works with simulated data. Getting real time data be in from Sensor or an Application, poses it own challenges and this is generally over looked while learning about machine learning.

This unique covers covers both Supervised machine learning and? Internet of things using Raspberry pi.

There is a growing demand for these kind of application, For example:

1. Building automation – Switch on Electrical device such as lighting and temperature control instrument when human being in present.

2. Attendance marking based on automatically identification of an employee.

3. Identify parking free parking lots.

4. Identify number plate in car.

5. Prevent Crime – Identify a person with criminal record.

6. And many more.

All these operate on combination of supervised learning technique coupled with IOT.

Hence this course covers supervised learning coupled with IOT?from a building building automation perspective. Once participants are clear about the concept they can then develop /extend it for other applications listed above or on the other machine learning algorithms.

Additionally, voice control IOT?application is also growing at a rapid pace. This course also covers topic related to building voice based IOT?application using Raspberry pi and other open source software and platforms like OPEN CV, Google assistant, Adafruit IO platform, IFTTT.

Happy learning!!!

Course Curriculum

Chapter 1: Prerequisite and Course coverage

Lecture 1: Prerequisite

Lecture 2: Course coverage

Chapter 2: Overview about Machine Learning

Lecture 1: Programming vs Machine learning

Lecture 2: Types of machine learning

Chapter 3: Machine learning and IOT – building block

Lecture 1: Machine learning and IOT – building block and boards

Lecture 2: IOT boards

Chapter 4: Preparing Raspberry pi3

Lecture 1: Rpi introduction and installing the Raspberry OS – Options-Rpi imager vs Manual

Lecture 2: Raspberry OS installation through Raspberry Imager tool – New & easy way!.

Lecture 3: Headless – Computer and Rpi3 configuration to connect through SSH via Ethernet.

Lecture 4: Rpi3 connection with Wifi

Lecture 5: Rpi3 headless connection through wifi

Chapter 5: Installation of OPENCV in Raspberry pi3

Lecture 1: Installation of OPENCV in Raspberry pi3 – Part1

Lecture 2: Installation of OPENCV in Raspberry pi3 – Part2

Chapter 6: Machine learning(Open CV) is Face and eye detection in images overview

Lecture 1: Face Detection using Open CV

Lecture 2: Face identification approach in machine learning

Chapter 7: Face and Eye detection in machine learning (Open CV) in Raspberry pi

Lecture 1: Open CV – Face detection program analysis

Lecture 2: Xming server – to view remote desktop GUI

Lecture 3: Demonstration – Face detection program execution

Lecture 4: Open CV – Haarcascade file path

Lecture 5: Open CV – Face and Eye detection program analysis

Lecture 6: Demonstration – Face and eye detection program execution

Chapter 8: Overview – Machine learning integration to IOT device

Lecture 1: Machine learning integration with IOT Overview

Lecture 2: Sensors and Actuators

Chapter 9: Raspberry pi as IOT device

Lecture 1: How to use Raspberry pi as IOT?

Lecture 2: Demonstration – LED blink program

Chapter 10: Detect face and SWITCH ON the Device

Lecture 1: Switch on the device, if face is detected

Lecture 2: Demonstration – Switch on the device, if face is detected

Chapter 11: Acquiring data from Sensor and from Web Api

Lecture 1: Overview about Sensor and Web Api integration

Lecture 2: Demonstration Program unit overview

Lecture 3: Demonstration of Sensor, Web Api

Chapter 12: Controlling IOT appliances through Adafruit web platform and through voice.

Lecture 1: Web and voice control overview

Lecture 2: Adafruit MQTT setup, install Adafruit library and code unit discussion

Lecture 3: Web control – Demonstration

Lecture 4: Voice integration control overview

Lecture 5: IFTTT Setup – Interface between Google assistance and Adafruit MQTT feed

Lecture 6: Google Assistant – Install overview

Lecture 7: Voice – web integrated control demonstration

Chapter 13: Prototype – Building automation IOT using Open CV

Lecture 1: Integrated prototype overview

Lecture 2: Prototype – Building automation IOT using Open CV -Demonstration

Chapter 14: ML – Supervisory learning – Identification of a person

Lecture 1: Identification of person – Supervisory learning- overview

Lecture 2: Walk through different program units

Lecture 3: Demo – Face recognition program

Lecture 4: Demo – Creation of supervisory model for prediction

Lecture 5: Demo – Face identification using supervisory model created

Chapter 15: Bonus Lecture

Lecture 1: Bonus

Instructors

Guha Rajan M., B.Engg, MBA
Founder and CEO – Capstone Solutions, Trainer

Rating Distribution

1 stars: 3 votes

2 stars: 2 votes

3 stars: 9 votes

4 stars: 9 votes

5 stars: 11 votes

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