Data Science:Deep Learning-CNN & OpenCV -Face Mask Detection

If you want to learn the process to detect whether a person is wearing a face mask using AI and Machine Learning algorithms then this course is for you.In this course I will cover, how to build a Face Mask Detection model to detect and predict whether a person is wearing a face mask or not in both static images and live video streams with very high accuracy using Deep Learning Models. This is a hands on project where I will teach you the step by step process in creating and evaluating a machine learning model using CNNs and OpenCV.This course will walk you through the initial data exploration and understanding, Data Augumentation, Data Generators, customizing pretrained Models like Mobile NetV2, model building and evaluation. Then using the trained model to detect the presence of face mask in images and video streams.I have splitted and segregated the entire course in Tasks below, for ease of understanding of what will be covered.Task 1  :  Project Overview.Task 2  :  Introduction to Google Colab.Task 3  :  Understanding the project folder structure.Task 4  :  Understanding the dataset and the folder structure.Task 5  :  Loading the data from Google Drive.Task 6  :  Importing the Libraries.Task 7  :  About Config and Resize File.Task 8  :  Some common Methods and Utilities Task 9  :  About Data Augmentation.Task 10 :  Implementing Data Augmentation techniques.Task 11 :  About Data Generators.Task 12 :  Implementing Data Generators.Task 13 :  About Convolutional Neural Network (CNNs).Task 14 :  About OpenCV.Task 15 :  Understanding pre-trained models.Task 1