Python Programming: Build a Recommendation Engine in Django

🚀 Python Programming: Build a Recommendation Engine in Djangocourse headline: 🎥 Collaborative Filtering with Python, Celery, Django, Worker Processes, Batch Predictions, SurpriseML, Keras, and more!

🚀 Course Overview:

Dive into the world of Python programming and learn to build a powerful recommendation engine using Django and Collaborative Filtering, a popular Machine Learning technique. This course will guide you through the process of creating a system that users can interact with, where they rate movies, and in return, receive personalized recommendations. 🎬💡

What You'll Learn:

• 🛠️ Working with Real Datasets: Load the MovieLens dataset into a SQL database using Django models, elevating your data handling skills beyond mere CSV operations.

• 🚀 Scalable Recommendation Systems: Understand how to handle batch inference by implementing the robust background worker process, Celery, which will enable your system to manage thousands of users efficiently.

• 🛠️ Mastering Batch Predictions: Discover how to perform batch predictions with SurpriseML and Keras, providing a solid foundation for scaling up your recommendation engine.

• ✨ Interactive Web Development: Use HTMX to dynamically update content on the web page without any JavaScript, enhancing user interaction in a more efficient way.

Course Structure Breakdown:

• 🌐 Web Process Setup: Learn how to set up Django to capture users' interests and deliver recommendations through a seamless web interface.

• 🤖 Machine Learning Pipeline: Extract, transform data from Django, train your Collaborative Filtering model, and get insights that will drive the recommendations.

• 🔧 Worker Process Glue: Utilize Celery to schedule, run, and manage background tasks that will process predictions and update the recommendation system in real-time.

Who Is This Course For?

This course is designed for individuals with a foundational understanding of Python (such as those who have completed 30 Days of Python) and familiarity with Django (for example, from Your First Django Web Project or Try Django 3.2). Prior experience with Celery can be helpful but is not mandatory, as we will cover the essentials in the course (check out Time & Tasks 2 or relevant blog posts for a head start).

Why Take This Course?

• Gain hands-on experience with real-world applications of Python and Django.

• Learn to manage large datasets and build systems that scale.

• Understand the inner workings of recommendation engines and how they can be implemented in a web context.

• Enhance your skills in machine learning with SurpriseML, Keras, and batch predictions.

• Implement advanced features using HTMX without relying on JavaScript.

By the end of this course, you'll have built a robust recommendation engine that can handle real-world user interactions, all while honing your Python, Django, and machine learning skills. 🌟 Ready to level up your programming knowledge and become an expert in building recommendation systems? Let's get started! Enroll now and embark on this exciting journey with Justin Mitchel as your guide. 🚀💻