Face Recognition with Machine Learning + Deploy Flask App

Course Headline: Master Face Recognition with Machine Learning & Deploy Your Flask App on Heroku 🚀

Course Description:

Embark on a journey to become proficient in creating a state-of-the-art face recognition web application using Python, OpenCV, and machine learning algorithms, with the final touch of deploying your application on Heroku. This course is meticulously designed for developers who aspire to build robust AI applications from scratch and make them accessible over the web. 🌐

MLOps: AI based Face Recognition Web App in Flask & Deploy

What you will learn? 🎓

• Python: Master the essential Python libraries and syntax needed for data manipulation and machine learning tasks.
• Image Processing with OpenCV: Learn to work with images using OpenCV, a powerful library that allows you to process video streams in real-time.
• Image Data Preprocessing: Understand how to prepare your image datasets for optimal processing and analysis.
• Image Data Analysis: Dive into the analysis of image data to extract meaningful features and insights.
• Eigenfaces with PCA: Explore principal component analysis (PCA) to reduce dimensionality and identify significant eigenfaces within the images.
• Face Recognition Classification Model with Support Vector Machines (SVM): Implement SVM for training a model capable of recognizing individual faces from image data.
• Pipeline Model: Create a pipeline for your machine learning workflow, enabling efficient handling of data and processing steps.
• Flask: Develop your web application using Flask, including setting up routes, using Jinja templates, and integrating HTML/CSS for a user-friendly interface.
• Develop Face Recognition Web App: Combine machine learning models with Flask to create a face recognition web application that can identify faces in real-time.
• Deploy Flask App in the Cloud (Heroku): Learn to deploy your Flask app on Heroku, ensuring your application is scalable and accessible from anywhere in the world. 🌟

Throughout this course, you will engage with hands-on projects that cover everything from image processing techniques in OpenCV to deploying your Flask app on cloud platforms like Heroku. You'll learn how to preprocess images, extract and compute features using PCA, train a machine learning model with SVM, and fine-tune it using the Grid search method for optimal hyperparameters.

By the end of this course, you will have developed a complete face recognition web application, successfully integrating your machine learning model into a Flask app and deploying it to the cloud. Your newfound skills will enable you to tackle the challenges of real-world AI applications, from data preprocessing to deployment, with confidence and expertise.

Join us now and transform your ideas into an interactive and intelligent face recognition web application that stands out in today's fast-paced tech environment! 🛠️✨

Prerequisites:

• Basic knowledge of Python programming
• Familiarity with the command line interface (CLI) for Linux/Unix systems

What You Need:

• A computer with internet access and the ability to install software
• Basic understanding of machine learning concepts

Course Outcome:

• A fully functional face recognition web application
• Deployment of your app on Heroku
• A strong foundation in integrating machine learning models into web applications using Flask

Get ready to build, learn, and deploy with this comprehensive course that bridges the gap between AI algorithms and real-world web applications! 🚀💻