Deploy Django + AI ML Face Recognition Web App in AWS | Udemy


Deploy Django + AI ML Face Recognition Web App in AWS | Udemy [Update 01/2024]
English | Size: 3.4 GB
Genre: eLearning

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

What you’ll 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

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 this course is for:

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