Building and Deploying Machine Learning Models

Welcome to the Course!

In this course, you will learn how to set up a development environment, build web applications with Streamlit, and deploy machine learning models using FastAPI.

What You Will Learn

This course is designed to provide a hands-on approach to:

1. Setting Up a Virtual Environment
   • Why virtual environments are important
   • Installing and managing dependencies
   • Using  pip for environment management
2. Building Web Apps with Streamlit & Model Deployment
   • Introduction to Streamlit
   • Creating interactive web applications
   • Integrating machine learning models into Streamlit
   • Deploying Streamlit apps
3. Building APIs with FastAPI & Model Deployment
   • Introduction to FastAPI
   • Learning API routes
   • Handling requests and responses
   • Deploying FastAPI applications

Prerequisites

Before starting this course, you should have:
✅ Basic knowledge of Python (functions, loops, modules)
✅ Familiarity with machine learning models
✅ A code editor, VS Code installed

Tools You Will Use

🔹 Python – The programming language for development
🔹 VS Code – The recommended code editor
🔹 Virtual Environments – To manage dependencies
🔹 Streamlit – For building interactive web apps
🔹 FastAPI – For creating high-performance APIs
🔹 Deployment Platforms – Streamlit Cloud, Heroku, or AWS