Chapter X: Model Deployment introduces you to deploying machine learning models into production environments. In this chapter, you’ll explore how to integrate your trained models into real-world applications using popular frameworks like Streamlit, Gradio, Flask, and FastAPI. Learn the steps for creating user-friendly interfaces, building robust APIs, and ensuring your models are scalable and accessible. This chapter will guide you through practical implementations, providing the tools and techniques to deploy your models confidently and efficiently.
What You’ll Learn
- The key concepts of model deployment and why it’s essential for real-world applications.
- How to use Streamlit and Gradio for creating interactive user interfaces for your models.
- Techniques for building and deploying APIs using Flask and FastAPI.
- How to ensure your models are scalable, performant, and production-ready.
- The process of integrating your models into business workflows for real-time solutions.
Why This Chapter?
- Perfect for learners looking to bring their machine learning models into production.
- Step-by-step guides with hands-on examples to help you deploy models with confidence.
- Gain practical experience deploying models with leading frameworks, ensuring you’re ready for real-world challenges.
