Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV
Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV, available at $34.99, has an average rating of 4.45, with 10 lectures, based on 241 reviews, and has 10704 subscribers.
You will learn about Get Hands-On Practice to classify whether a person is wearing a Face Mask or not using Deep Learning & OpenCV Make Predictive Analysis on the static images as well as in the videos to detect face masks Learn to Build and Train Convolutional Neural Network Model Learn to Test CNN models and analyze their performances This course is ideal for individuals who are Anyone interested in Deep Learning or Someone who wants to learn to build Convolutional Neural Network for Image Classification or Someone who wants to use AI to detect face masks on the images as well as in the video streams or Anyone who wants to learn to Build, Train & Test Convolutional Neural Network Models It is particularly useful for Anyone interested in Deep Learning or Someone who wants to learn to build Convolutional Neural Network for Image Classification or Someone who wants to use AI to detect face masks on the images as well as in the video streams or Anyone who wants to learn to Build, Train & Test Convolutional Neural Network Models.
Enroll now: Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV
Summary
Title: Data Science:Hands-on Covid19 Face Mask Detection-CNN&OpenCV
Price: $34.99
Average Rating: 4.45
Number of Lectures: 10
Number of Published Lectures: 10
Number of Curriculum Items: 10
Number of Published Curriculum Objects: 10
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- Get Hands-On Practice to classify whether a person is wearing a Face Mask or not using Deep Learning & OpenCV
- Make Predictive Analysis on the static images as well as in the videos to detect face masks
- Learn to Build and Train Convolutional Neural Network Model
- Learn to Test CNN models and analyze their performances
Who Should Attend
- Anyone interested in Deep Learning
- Someone who wants to learn to build Convolutional Neural Network for Image Classification
- Someone who wants to use AI to detect face masks on the images as well as in the video streams
- Anyone who wants to learn to Build, Train & Test Convolutional Neural Network Models
Target Audiences
- Anyone interested in Deep Learning
- Someone who wants to learn to build Convolutional Neural Network for Image Classification
- Someone who wants to use AI to detect face masks on the images as well as in the video streams
- Anyone who wants to learn to Build, Train & Test Convolutional Neural Network Models
Would you like to learn how to detect if someone is wearing a Face Mask or not using Artificial Intelligence that can be deployed in bus stations, airports, or other public places?
Would you like to build a Convolutional Neural Network model using Deep learning to detect Covid-19 Face Mask?
If the answer to any of the above questions is “YES”,then this course is for you.
Enroll Now in this course and learn how to detect Face Mask on the static images as well as in the video streams using Tensorflow and OpenCV.
As we know, COVID-19 has affected the whole world very badly. It has a huge impact on our everyday life, and this crisis is increasing day by day. In the near future, it seems difficult to eradicate this virus completely.
To counter this virus, Face Masks have become an integral part of our lives. These Masks are capable of stopping the spread of this deadly virus, which will help to control the spread. As we have started moving forward in this ‘new normal’ world, the necessity of the face mask has increased. So here, we are going to build a model that will be able to classify whether the person is wearing a mask or not. This model can be used in crowded areas like Malls, Bus stands, and other public places.
This is a hands-on Data Science guided project on Covid-19 Face Mask Detection using Deep Learning and Computer Vision concepts. We will build a Convolutional Neural Network classifier to classify people based on whether they are wearing masks or not and we will make use of OpenCV to detect human faces on the video streams. No unnecessary lectures. As our students like to say :
“Short, sweet, to the point course”
The same techniques can be used in :
Skin cancer detection
Normal pneumonia detection
Brain defect analysis
Retinal Image Analysis
Enroll now andYou will receive a CERTIFICATE OF COMPLETION and we encourage you to add this project to your resume. At a time when the entire world is troubled by Coronavirus, this project can catapult your career to another level.
So bring your laptop and start building, training and testing the Data Science Covid 19 Convolutional Neural Network model right now.
You will learn:
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How to detect Face masks on the static images as well as in the video streams.
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Classify people who are wearing masks or not using deep learning
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Learn to Build and train a Convolutional neural network
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Make a prediction on new data using the trained CNN Model
We will be completing the following tasks:
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Task 1: Getting Introduced to Google Colab Environment & importing necessary libraries
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Task 2: Downloading the dataset directly from the Kagge to the Colab environment.
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Task :3 Data visualization (Image Visualization)
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Task 4: Data augmentation & Normalization
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Task 5: Building Convolutional neural network model
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Task 6: Compiling & Training CNN Model
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Task 7: Performance evaluation & Testing the model & saving the model for future use
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Task 8: Make use of the trained model to detect face masks on the static image uploaded from the local system
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Task 9: Make use of the trained model to detect face masks on the video streams
So, grab a coffee, turn on your laptop, click on the ENROLL NOW button, and start learning right now.
Course Curriculum
Chapter 1: Project Overview & Import Libraries
Lecture 1: Project Overview
Lecture 2: Introduction to Google Colab & Import libraries
Chapter 2: Download and explore the dataset
Lecture 1: Overview of the structure of directories
Lecture 2: Download Mask dataset directly from the Kaggle Platform
Chapter 3: Image Visualization
Lecture 1: Image Visualization using Matplotlib
Chapter 4: Data Augmentation
Lecture 1: Image Augmentation
Chapter 5: Build the Convolutional Neural Network
Lecture 1: Build the Convolutional Neural Network from scratch
Chapter 6: Train & Evaluate performance of the model
Lecture 1: Compile, Train and evaluate the performance of the model
Chapter 7: Use of trained model to detect face masks on the static images
Lecture 1: Make use of trained model to detect face masks on the static images
Chapter 8: Use of trained model and OpenCV to detect face masks on the video streams
Lecture 1: Make use of trained model to detect face masks on the video streams
Instructors
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School of Disruptive Innovation
Creative Learning Solutions for the Digital Age
Rating Distribution
- 1 stars: 5 votes
- 2 stars: 9 votes
- 3 stars: 32 votes
- 4 stars: 89 votes
- 5 stars: 106 votes
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