Ryan Day | Hands-On APIs for AI and Data Science. Python Development with FastAPI (2025) [PDF, EPUB]
Автор: Ryan Day
Издательство: O'Reilly Media
ISBN: 978-1098164379, 978-1-098-16441-6
Жанр: Web Services & APIs, Web Services, Web Programming
Язык: Английский
Формат: PDF, EPUB
Качество: Изначально электронное (ebook)
Иллюстрации: Цветные и черно-белые
Описание:Are you ready to grow your skills in AI and data science? A great place to start is learning to build and use APIs in real-world data and AI projects. API skills have become essential for AI and data science success, because they are used in a variety of ways in these fields. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit.
As you complete the chapters in the book, you'll be creating portfolio projects that teach you how to:
Design APIs that data scientists and AIs love
Develop APIs using Python and FastAPI
Deploy APIs using multiple cloud providers
Create data science projects such as visualizations and models using APIs as a data source
Access APIs using generative AI and LLMs
Part I: Building APIs for Data Science
Chapter 1: Creating APIs That Data Scientists Will Love – Designing for data scientist needs and identifying user stories.
Chapter 2: Selecting Your API Architecture – Exploring REST, GraphQL, and gRPC architectural styles.
Chapter 3: Creating Your Database – Using SQLite and SQLAlchemy to build and test database tables.
Chapter 4: Developing the FastAPI Code – Core implementation using FastAPI, Pydantic, and Uvicorn.
Chapter 5: Documenting Your API – Utilizing Swagger UI and Redoc for automated documentation.
Chapter 6: Deploying Your API to the Cloud – Deployment strategies using Docker, Render, and AWS Lightsail.
Chapter 7: Batteries Included: Creating a Python SDK – Building client-side SDKs to simplify API consumption.
Part II: Using APIs in Your Data Science Project
Chapter 8: What Data Scientists Should Know About APIs – Core principles like separation of concerns and version control.
Chapter 9: Using APIs for Data Analytics – Extracting data into Jupyter Notebooks and pandas for custom metrics.
Chapter 10: Using APIs in Data Pipelines – Orchestrating data movement with Apache Airflow.
Chapter 11: Using APIs in Streamlit Data Apps – Creating interactive dashboards and visualizations.
Part III: Using APIs with Artificial Intelligence
Chapter 12: Using APIs with Artificial Intelligence – Intersection of generative AI, LLMs, and agentic applications.
Chapter 13: Deploying a Machine Learning API – Training and serving models with scikit-learn and ONNX Runtime.
Chapter 14: Using APIs with LangChain – Building AI agents that call APIs using LangGraph and LangChain.
Chapter 15: Using ChatGPT to Call Your API – Integrating custom GPTs with your API through GPT Actions
Скриншоты:
Время раздачи: с 10 до 20 (минимум до появления первых 3-5 скачавших) 
