Python/Django App- Create & Deploy a Computer Vision Model

GroupLayout: Mastering Full Stack Computer Vision with Python & Django

🚀 Course Headline: [Unlock the Power of AI] - Build, Train & Deploy Your Own Computer Vision Model with Python/Django

👩‍💻 Instructor: Ashar Siddiqui

🌍 About the Course: This comprehensive course is tailored for developers who have a solid understanding of machine learning and deep learning concepts but are looking to bridge the gap between training models and deploying them in a full-fledged web application. Whether you're a software engineer, a data scientist, or an AI enthusiast, this course will guide you through the process of creating a state-of-the-art computer vision model using Python, leveraging transfer learning with CNNs (Convolutional Neural Networks) in Keras, and then deploying your model within a scalable Django web application.

🔍 Course Description: Who should take this course? This course is perfect for you if:

• You can train ML/DL models but don't know how to save or use them later.
• You're familiar with the basics of Python and have a foundational understanding of Django.
• You want to learn how to deploy machine learning models in a production environment.
• You aim to build a computer vision application that is both powerful and user-friendly.

What will you learn? By the end of this course, you'll be able to:

• Create Computer Vision Models from Scratch: Learn the fundamentals of building a model using libraries like TensorFlow and Keras.
• Utilize Transfer Learning: Understand how to use pre-trained models for feature extraction to boost your application's performance with minimal data.
• Save Your Model: Discover methods to save your trained model so it can be used in production without retraining.
• Set Up Your Development Environment: Get your development environment ready for building web applications using Python and Django.
• Develop a Full Stack Application: Build a full stack web application that interacts with your computer vision model through HTML, CSS, JavaScript, and AJAX.
• Deploy Your Model: Learn the best practices for deploying your machine learning model within a Django web app.
• Ensure Scalability and Performance: Ensure your application can handle various loads and perform well under different conditions.

Course Highlights:

• Real-World Project: You will work on a real project that involves collecting data, building a model, saving it, and deploying it within a full stack Django app.
• Hands-On Learning: This course is packed with coding exercises and projects that reinforce the concepts taught.
• Expert Guidance: Learn from Ashar Siddiqui's expert guidance, who will provide insights and real-world examples to support your learning journey.

What's Inside: ⚫️ Module 1: Introduction to Computer Vision & Python Libraries

• Understanding the basics of computer vision.
• Setting up Python and essential libraries (OpenCV, NumPy, etc.).

⚫️ Module 2: Building Your First Computer Vision Model

• Analyzing dataset and preprocessing data.
• Crafting a model architecture with Keras.
• Training your first model from scratch.

⚫️ Module 3: Leveraging Transfer Learning & Pre-trained Models

• Exploring the concept of transfer learning.
• Using pre-trained models for feature extraction.
• Fine-tuning pre-trained models for your specific use case.

⚫️ Module 4: Saving Your Model

• Learning how to save and load models using Python's 'pickle' module.
• Ensuring that your model can be easily retrieved and used without retraining.

⚫️ Module 5: Building the Web Application Interface

• Creating a user-friendly interface for your application with HTML, CSS, and JavaScript.
• Implementing AJAX to enable asynchronous requests to your model.

⚫️ Module 6: Setting Up Django Framework

• Understanding the Django framework and its advantages.
• Building a scalable, maintainable web application with Django.

⚫️ Module 7: Deploying Your Model with Django

• Integrating your machine learning model into the Django application.
• Deploying your Django app to a production server.

🚀 What's Next? After completing this course, you will be equipped with the skills to build, train, and deploy full-stack computer vision models using Python and Django. You'll have a solid understanding of how to leverage machine learning in real-world applications, making you a valuable asset in the field of AI development. 🚀

🔑 Unlock Your Full Stack Potential: Enroll now and take your first step towards mastering full stack computer vision development with Python and Django! 🌟