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Description of  Ml Model Deployment With Fastapi And Streamlit

Published 3/2024 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 1.98 GB | Duration: 4h 38m FastAPI and Streamlit Essentials for ML Model Deployment What you'll learn Develop and deploy robust REST APIs with FastAPI for your ML models. Build interactive and user-friendly interfaces for interacting with your models using Streamlit. Deploy your ML applications on various platforms. Implement best practices for secure and scalable ML deployment. Showcase your ML models as interactive web applications for presentations or portfolio building. Requirements Basic understanding of Python such as data types, data structures, functions and classes. Basic understanding of data science concepts like how to perform EDA and build a model. Description Overview Section 1: Introduction Lecture 1 Synopsis Lecture 2 What is Model Deployment? Lecture 3 Model Deployment Strategies Lecture 4 Overview of FastAPI and Streamlit Section 2: Building APIs with FastAPI Lecture 5 Section Overview Lecture 6 Path Parameters Lecture 7 Query Parameters Lecture 8 Request Body Lecture 9 Input Validations Lecture 10 Request Body Validations Lecture 11 Forms and Files Lecture 12 Response Status Codes Lecture 13 Templates and Static Files Lecture 14 Testing Section 3: ML Models as an API with FastAPI Lecture 15 Section Overview Lecture 16 Project Structure Lecture 17 Building the ML Model Lecture 18 Model API Endpoints Lecture 19 User Interface Lecture 20 Testing Section 4: Building Web Applications with Streamlit Lecture 21 Section Overview Lecture 22 Displaying Data Lecture 23 Widgets Lecture 24 Layout Lecture 25 Caching Lecture 26 Session State Lecture 27 Paging Section 5: Integrating FastAPI with Streamlit Lecture 28 Section Overview Lecture 29 Project Structure Lecture 31 Integrating API Endpoint with Streamlit Section 6: Deployment Lecture 32 Deploying FastAPI on Render Lecture 33 Deploying Streamlit App on Streamlit Section 7: WhatsApp AI Text-to-Image Chatbot Lecture 34 Introduction Lecture 35 Setting Up Project Directory Lecture 36 Connecting to Vonage Lecture 37 Connecting to OpenAI API Lecture 38 Building the FastAPI Application Section 8: Capstone Project Section 9: BONUS Section Lecture 39 Bonus Lecture