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CodeSignal

Model Serving with FastAPI

via CodeSignal

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Overview

In this course, learners transition to model serving by integrating their ML model into a web service using FastAPI. The focus is on creating a functional API that leverages the model persistence function from Course 1 and ensures that the prediction endpoint is both robust and secure.

Syllabus

  • Unit 1: Building a Basic FastAPI Application for Diamond Price Prediction
    • Setting Up FastAPI Metadata
    • Enhance Your FastAPI Root Endpoint
    • Enhance Your API Health Check
    • Running Your API with Uvicorn
    • Enhance API with Asynchronous Endpoints
    • Building a FastAPI Application
  • Unit 2: Integrating Machine Learning Models with FastAPI for Predictions
    • Converting Features for Prediction
    • Loading and Managing ML Models
    • Defining Diamond Data Structure
    • Dependency Injection with FastAPI
    • Enhance API Response Structure
    • Create a Diamond Price Predictor
  • Unit 3: Testing FastAPI Applications with pytest
    • Testing FastAPI with Pytest
    • Testing Your API's Welcome Message
    • Mocking Models with Pytest Fixtures
    • Testing API Resilience with Invalid Inputs
    • Testing Predict Endpoint with Valid Inputs

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