Book Image

Learn Python by Building Data Science Applications

By : Philipp Kats, David Katz
Book Image

Learn Python by Building Data Science Applications

By: Philipp Kats, David Katz

Overview of this book

Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production. This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice. By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.
Table of Contents (26 chapters)
Free Chapter
1
Section 1: Getting Started with Python
11
Section 2: Hands-On with Data
17
Section 3: Moving to Production

Chapter 19

What does a serverless application mean?

Serverless applications still run on normal servers, but control over the server's behavior and the stack are completely handled by the cloud provider—all that's required from the developer is to write a function that describes the business logic. This function can be set to trigger on a request to a certain API endpoint, on a certain event (for example, a file addition to the S3 bucket), or on a scheduler so that it runs every day.

What are the limitations of the serverless approach?

Serverless applications are mainly bound by the memory they can use and, therefore, the packages that can be installed. For AWS Lambda, the limit is 50 MB.

What are the benefits of serverless APIs?

Serverless APIs have quite a few benefits. First and foremost, you don't need to spend time on the development and maintenance...