Deploy Django + AI ML Face Recognition Web App in AWS

🚀 Course Title: Deploy Django + AI ML Face Recognition Web App in AWS 🌟

Course Headline:

🚀 Develop & Deploy Face Recognition & Facial Emotion using OpenCV, Machine Learning, Django, Database in Python on AWS! 🛠️✨

Course Description:

Welcome to the AI and ML Enthusiast Course: Building a Face Recognition Web App with Django, Machine Learning, and Cloud Deployment on AWS! This is your invitation to an exhilarating voyage into the world of Artificial Intelligence, specifically focusing on Computer Vision and Face Recognition. Our comprehensive course is tailored to guide you through the entire lifecycle of a project, serving as the perfect blend for enthusiasts of both machine learning and web development. 🤖🌍

Course Phases:

Phase 1: Machine Learning - Face Identity Recognition

• Image processing with OpenCV: Dive into the fundamentals of image processing, understanding how to manipulate and analyze images using OpenCV.

• Prerequisites: Get your Python environment ready with the necessary libraries and dependencies.

• Face Detection: Learn how to detect faces within images and videos using OpenCV and Deep Neural Networks.

• Feature Extraction: Extract meaningful features from detected faces for further processing.

• Machine Learning Models: Explore various models like logistic regression, support vector machines, and random forest.

• Voting Classifier: Combine multiple models using the voting classifier technique to improve model performance.

• Model Selection & Hyperparameter Tuning: Fine-tune your model for optimal performance in face recognition tasks.

Phase 2: Machine Learning - Facial Emotion Recognition

• Application of Techniques: Apply the knowledge gained from the face identity recognition phase to recognize facial emotions.

• Integration into Pipeline: Seamlessly integrate detection and recognition models into a robust pipeline.

Phase 3: Django Web App Development

• Django Web Application: Build a full-fledged web application using the Django framework.

• Frontend Rendering: Utilize HTML, CSS, and Bootstrap to create an appealing user interface.

• Backend Development: Develop your backend using Python's MVT (Models, Views, and Templates) approach.

• Database Design: Set up a SQLite database that interacts with your Django app.

• Machine Learning Integration: Interface your machine learning pipeline models with the Django application.

• Bootstrap Styling: Enhance your app's aesthetics and usability using Bootstrap components.

Phase 4: Deployment / Production on AWS Cloud

• AWS Elastic Beanstalk Deployment: Learn how to deploy your Django web app onto AWS Elastic Beanstalk with ease.

• AWS Free Tier: Utilize the AWS Free Tier to ensure your project stays within budget for the first year.

• Global Accessibility: Make your application accessible worldwide by deploying it on a cloud platform.

• Troubleshooting & Error Resolution: Master deployment by troubleshooting common issues and resolving errors during the deployment process.

Course Highlights:

• OpenCV Mastery: Gain a deep understanding of OpenCV for effective image processing tasks.

• Machine Learning Models: Train models specifically for Face Recognition and Facial Emotion Recognition.

• Django Web App Development: Learn the ins and outs of Django, from concept to production.

• Integration of AI into Django: Integrate your trained machine learning models with a Django web app.

• Cloud Deployment on AWS: Focus on deploying your application using AWS Elastic Beanstalk while leveraging the AWS Free Tier.

Embark on this journey to master AI and ML concepts with practical, hands-on experience. Whether you're a seasoned developer or new to the field, this course equips you with the tools and knowledge to deploy a sophisticated Face Recognition Web App powered by Django and AWS. 🤝

Don't let this opportunity pass you by! Join us inside the course and unlock your potential as an AI developer. 🚀

See you inside, and let's make your AI project come to life on the cloud with AWS! 🎉