Author: Deep Learner

Python

Building Python Project Documentation With MkDocs

In this course, you’ll learn how to quickly build documentation for a Python package using MkDocs and mkdocstrings. These tools allow you to generate nice-looking and modern documentation from Markdown files and your code’s docstrings. Maintaining auto-generated documentation means less effort because you’re linking information between your code and the documentation pages. However, good documentation is more than just the technical description pulled from your code! Your project will appeal more to users if you guide them through examples and […]

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Python

Connecting the dots — SML

I was working on a paper titled “Web services learning Bot: A responsive, actionable AIML BOT Framework.” during my sophomore year. The bot discussed in this paper is based on AIML, a simple language for crafting conversational agents that anyone could learn, interpret, or extend.

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Python

Django 4.1: Improving Database Accessibility

Introduction Today’s commodity in all applications, written by all manner of different programming languages, is speed. For example, how fast we get our render, send our information, process complex operations, or in general, how fluent is the whole experience while using an application. We’ve developed a certain standard we expect from our applications. So how do we maintain that standard with    

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Python

When Do You Use an Ellipsis in Python?

In English writing, you can use the ellipsis to indicate that you’re leaving something out. Essentially, you use three dots (…) to replace the content. But the ellipsis doesn’t only exist in prose—you may have seen three dots in Python source code, too. The ellipsis literal (…) evaluates to Python’s Ellipsis. Because Ellipsis is a built-in constant, you can use Ellipsis or … without importing it: >>> >>> … Ellipsis >>> Ellipsis Ellipsis >>> … is Ellipsis True Although three […]

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AI Models vs. AI Systems: Understanding Units of Performance Assessment

As AI becomes more deeply integrated into every aspect of our lives, it is essential that AI systems perform appropriately for their intended use. We know AI models can never be perfect, so how do we decide when AI performance is ‘good enough’ for use in a real life application? Is level of accuracy a sufficient gauge? What else matters? These are questions Microsoft Research tackles every day as part of our mission to follow a responsible, human-centered approach to […]

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