Learn how to deploy your ML models into production with confidence by load testing your APIs in Python with Flask and Locust

Deploying with confidence

Deploying a Machine Learning (ML) model as a live service to be consumed by a business-critical system or directly by end-users can be a scary prospect. The more in-demand the system, the higher the risk that issues with your model may disrupt it. However, you also can’t keep your models…

Data scientists: choosing whether to join a startup is a big decision. Here’s some advice to help you figure out whether life at a startup is for you.

This post is (as the title might suggest) inspired by Chip Huyen’s ‘7 reasons not to join a startup and 1 reason to’ post. While reading it, I was reminded of several conversations I’ve had over the last year or so with various ML practitioners inside and outside of startups…

Getting APIs into production can be a bewildering prospect. This post gives you tips and a template for using Flask in production.

What is Flask?

If you work in the world of (or a world adjacent to) cloud software and are familiar with Python, the chances are you’ll have come across Flask — the excellent, minimal ‘ micro’ web framework that’s been at the heart of the Python web community for around a decade. It…

In Part 1 of this series, you saw a few practical examples of how Object-Oriented Programming (OOP) can be used to help you resolve some code design problems. If you missed it, it’s over here:

Right, let’s dig in.

Getting technical

The language around OOP can seem intimidating. You’ve seen some of…

Mark Douthwaite

Applied AI specialist, computer scientist, software engineer. Read more at https://mark.douthwaite.io/

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