You're reading from Building Data Science Applications with FastAPI

Product typeBook

Published inOct 2021

Reading LevelBeginner

PublisherPackt

ISBN-139781801079211

Edition1st Edition

Languages

Python

Tools

Fastlane

Concepts

Data Science

Author (1)

François Voron

Summary

Great! You now have a grasp of the ins and outs of NumPy and pandas. Basically, those libraries are the essential tool for data scientists in Python. By relying on optimized and compiled code, they allow you to load and manipulate large set of data in Python, without sacrificing performance. To allow this, they define fixed-type data structures, meaning each value in the dataset should be of the same type. This is what enables efficient memory consumption and fast computations.

Even though those basics should be enough for you to get started, we recommend that you spend some time on the official user guides and tinker with those a bit to discover all their aspects.

As we said in the introduction, NumPy and pandas are at the heart of most data science applications in Python. In the next chapter, we'll see how they will help us in machine learning tasks, along with the well-known machine learning library scikit-learn.

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Building Data Science Applications with FastAPI

Published in: Oct 2021Publisher: PacktISBN-13: 9781801079211

Author (1)

François Voron

François Voron graduated from the University of Saint-Étienne (France) and the University of Alicante (Spain) with a master's degree in machine learning and data mining. A full stack web developer and a data scientist, François has a proven track record working in the SaaS industry, with a special focus on Python backends and REST APIs. He is also the creator and maintainer of FastAPI Users, the #1 authentication library for FastAPI, and is one of the top experts in the FastAPI community.
Read more about François Voron

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