Building data science applications with FastAPI : develop, manage, and deploy efficient machine learning applications with Python /

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Get well-versed with FastAPI features and best practices for testing, monitoring, and deployment to run high-quality and robust data science applications Key Features Cover the concepts of the FastAPI framework, including aspects relating to asynchronous programming, type hinting, and dependency inj...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Voron, Francois (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Birmingham : Packt Publishing, 2021.
Temas:
Data mining > Computer programs.
Python (Computer program language)
Application program interfaces (Computer software)
Data mining.
Data Mining
Python (Langage de programmation)
Exploration de données (Informatique)
Exploration de données (Informatique) > Logiciels.
Interfaces de programmation d'applications.
APIs (interfaces)
Data mining
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)
Tabla de Contenidos:
  • Table of Contents Python Development Environment Setup Python Programming Specificities Developing RESTful API with FastAPI Managing pydantic Data Models in FastAPI Dependency Injections in FastAPI Databases and Asynchronous ORMs Managing Authentication and Security in FastAPI Defining WebSockets for Two-Way Interactive Communication in FastAPI Testing an API Asynchronously with pytest and HTTPX Deploying a FastAPI Project Introduction to NumPy and Pandas Training Machine Learning Models with scikit-learn Creating an Efficient Prediction API Endpoint with FastAPI Implement a Real-Time Face Detection System Using WebSockets with FastAPI and OpenCV.

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