Python

Primer on Python Decorators

In this tutorial on Python decorators, you’ll learn what they are and how to create and use them. Decorators provide a simple syntax for calling higher-order functions. By definition, a decorator is a function that takes another function and extends the behavior of the latter function without explicitly modifying it. This sounds confusing, but it’ll make more sense after you’ve seen a few examples of how decorators work. You can find all the examples from this tutorial by downloading the […]

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Machine Learning

Multiprocessing in Python

When you work on a computer vision project, you probably need to preprocess a lot of image data. This is time-consuming, and it would be great if you could process multiple images in parallel. Multiprocessing is the ability of a system to run multiple processors at one time. If you had a computer with a single processor, it would switch between multiple processes to keep all of them running. However, most computers today have at least a multi-core processor, allowing […]

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Machine Learning

Google Colab for Machine Learning Projects

Have you ever wanted an easy-to-configure interactive environment to run your machine learning code that came with access to GPUs for free? Google Colab is the answer you’ve been looking for. It is a convenient and easy-to-use way to run Jupyter notebooks on the cloud, and their free version comes with some limited access to GPUs as well. If you’re familiar with Jupyter notebooks, learning Colab will be a piece of cake, and we can even import Jupyter notebooks to […]

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Machine Learning

Mastering Pair Plots for Visualization and Hypothesis Creation in the Ames Housing Market

Navigating the complex landscape of real estate analytics involves unraveling distinct narratives shaped by various property features within the housing market data. Our exploration today takes us into the realm of a potent yet frequently overlooked data visualization tool: the pair plot. This versatile graphic not only sheds light on the robustness and orientation of connections between features and sale prices but also provides a holistic perspective on the dynamics among different features within the dataset. Let’s get started. Mastering […]

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Python

How to Write Beautiful Python Code With PEP 8

PEP 8, sometimes spelled PEP8 or PEP-8, is a document that provides guidelines and best practices on how to write Python code. It was written in 2001 by Guido van Rossum, Barry Warsaw, and Alyssa Coghlan. The primary focus of PEP 8 is to improve the readability and consistency of Python code. By the end of this tutorial, you’ll be able to: Write Python code that conforms to PEP 8 Understand the reasoning behind the guidelines laid out in PEP […]

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Artificial intelligence Leave a comment

Research Focus: Week of February 5, 2024

Welcome to Research Focus, a series of blog posts that highlights notable publications, events, code/datasets, new hires and other milestones from across the research community at Microsoft. EVENT RECAP Microsoft Research Forum series kicks off with focus on the promise and challenges of AI With a look back at the incredible changes of 2023 and a look ahead at the tangible advances to come, the inaugural Microsoft Research Forum explored bold new ideas and  

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Neural Machine Translation (NMT), NMT Leave a comment

Highlights from Machine Translation and Multilinguality in December 2023 and January 2024

Many things happened in the field in December: EMNLP, Google released Gemini, and Mixtral appeared. January was seemingly not that packed with new events, but plenty of new interesting work popped up on arXiv. Predicting Human Translation Difficulty with Neural Machine Translation Folks from the University of Melbourne found out that features from NMT, most notably the target sentence perplexity and something they call flow features, are a good predictor of human translation time. Turning English-centric LLMs Into Polyglots: How […]

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Python

Python Basics Exercises: Lists and Tuples

In Python Basics: Lists and Tuples, you learned that Python lists resemble real-life lists in many ways. They serve as containers for organizing and storing collections of objects, allowing for the inclusion of different data types. You also learned about tuples, which are also collections of objects. However, while lists are mutable, tuples are immutable. In this Python Basics Exercises course, you’ll test and reinforce your knowledge of Python lists and tuples. Along the way, you’ll also get experience with […]

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Machine Learning

Feature Relationships 101: Lessons from the Ames Housing Data

In the realm of real estate, understanding the intricacies of property features and their impact on sale prices is paramount. In this exploration, we’ll dive deep into the Ames Housing dataset, shedding light on the relationships between various features and their correlation with the sale price. Harnessing the power of data visualization, we’ll unveil patterns, trends, and insights that can guide stakeholders from homeowners to real estate developers. Let’s get started. Feature Relationships 101: Lessons from the Ames Housing DataPhoto […]

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