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    Face Recognition Web App with Machine Learning in Flask

    Posted By: lucky_aut
    Face Recognition Web App with Machine Learning in Flask

    Face Recognition Web App with Machine Learning in Flask
    Duration: 9h 27m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.43 GB
    Genre: eLearning | Language: English

    Create an Face Recognition (AI) project from scratch with Python, OpenCV , Machine Learning Algorithms and Flask

    What you'll learn
    Automatic Face Recognition in images and videos
    Automatically detect faces from images and videos
    Evaluate and Tune Machine Learning
    Building Machine Learning Model for Classification
    Make Pipeline Model for deploying your application
    Image Processing with OpenCV
    Data Preprocessing for Images
    Create REST APIs in Flask
    Template Inheritance in Flask
    Integrating Machine Learning Model in Flask App

    Requirements
    Should be at-least beginner level in Python
    Be able to understand HTML and CSS
    Basic Understanding of Machine Learning Concepts

    Description
    Face Recognition Web Project using Machine Learning in Flask Python

    Face recognition is one of the most widely used in my application. If at all you want to develop and deploy the application on the web only knowledge of machine learning or deep learning is not enough. You also need to know the creation of pipeline architecture and call it from the client-side, HTTP request, and many more. While doing so you might face many challenges while developing the app. This course is structured in such a way that you can able to develop the face recognition based web app from scratch.

    What you will learn?

    Python

    Image Processing with OpenCV

    Image Data Preprocessing

    Image Data Analysis

    Eigenfaces with PCA

    Face Recognition Classification Model with Support Vector Machines

    Pipeline Model

    Flask (Jinja Template, HTML, CSS, HTTP Methods)

    Finally, Face recognition Web App



    You will learn image processing techniques in OpenCV and the concepts behind the images. We will also do the necessary image analysis and required preprocessing steps for images.

    For the preprocess images, we will extract features from the images, ie. computing Eigen images using principal component analysis. With Eigen images, we will train the Machine learning model and also learn to test our model before deploying, to get the best results from the model we will tune with the Grid search method for the best hyperparameters.

    Once our machine learning model is ready, will we learn and develop a web server gateway interphase in flask by rendering HTML CSS and bootstrap in the frontend and in the backend written in Python. Finally, we will create the project on the Face Recognition project by integrating the machine learning model to Flask App.

    Who this course is for:
    Any one who want to learn image processing and build data science applications
    Beginners on Python who want to data science project
    Who want to start their career in artificial intelligence and data science
    Data science beginner who want to build end to end data science project

    More Info