Deploy Django + AI ML Face Recognition Web App in AWS

Develop & Deploy Face Recognition, Facial Emotion using OpenCV, Machine Learning, Django, Database in Python in AWS

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Deploy Django + AI ML Face Recognition Web App in AWS

What You Will Learn!

  • Deploy Face Recognition Django Web App in AWS and Heroku Cloud
  • Train your own Machine Learning based Face Recognition Model in Python
  • Train own Facial Emotion Recognition using Machine Learning in Python
  • Develop Django Web App using MVT Framework
  • Design SQLlite Database in Django
  • Train Support Vector Machines, Random Forest Model for Face Recognition in Python
  • Debuging error while Deploying in Heroku
  • Interphase Machine Learning Models with MVT Framework
  • Build Ensemble (stacking) Machine Learning Model combining SVM and Random Forest Models in Python
  • Face Detection with Deep Neural Networks
  • OpenCV Essentials for Face Recognition
  • Managing Heroku Cloud
  • Styling Django Web App with Bootstrap

Description

Welcome to the AI and ML Enthusiast Course: Building a Face Recognition Web App with Django, Machine Learning, and Cloud Deployment on AWS!

Embark on an exciting journey into Artificial Intelligence as we delve into the realms of Computer Vision and Face Recognition within the expansive field of AI and ML. This course is designed to guide you through the entire development process of an end-to-end project, catering to both machine learning and web development enthusiasts.

Course Phases:

Phase 1: Machine Learning - Face Identity Recognition

  • Image processing techniques with OpenCV

  • Prerequisites of the course: Python installation and library setup

  • Face Detection using OpenCV and Deep Neural Networks

  • Feature extraction using deep neural networks

  • Training machine learning models: logistic regression, support vector machines, random forest

  • Combining models with a Voting Classifier (stacking method)

  • Model selection and hyperparameter tuning for face recognition

Phase 2: Machine Learning - Facial Emotion Recognition

  • Application of machine learning techniques from face identity recognition

  • Integration of detection and recognition models into a pipeline

Phase 3: Django Web App Development

  • Web application development in Django

  • Rendering HTML, CSS, and Bootstrap for the frontend

  • Backend development in Python using the MVT (Models, Views, and Templates) framework

  • Designing a SQLite database for the Django app

  • Interfacing machine learning pipeline models with the MVT framework

  • Styling the app using Bootstrap

Phase 4: Deployment / Production on AWS Cloud

  • Deployment of the Django Web App on AWS Elastic Beanstalk

  • Utilizing the AWS Free Tier for 12 months

  • Accessing the app globally through a provided URL/domain

  • Troubleshooting and error resolution during deployment

Course Highlights:

  • In-depth learning of OpenCV for image processing

  • Training models for Face Recognition and Facial Emotion Recognition

  • Django web app development with MVT framework

  • Integration of machine learning models into the web app

  • Deployment on AWS Elastic Beanstalk with a focus on the AWS Free Tier

If you aspire to be an AI developer, this course is your gateway to mastering AI and ML concepts while gaining hands-on experience. Don't miss out – start your journey now!

See you inside the course!

Who Should Attend!

  • Anyone who want to learn OpenCV project
  • Python Developers curious about Artificial Intelligence Projects

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Tags

  • Django
  • Web Development
  • Face Detection

Subscribers

3038

Lectures

104

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