Python

What can you do about climate change?

Climate change is impacting the whole planet, and getting worse every year. So you want to do something—but you’re not sure what. If you do some research you might encounter an essay by Bret Victor—What can a technologist do about climate change? There’s a whole pile of good ideas in there, and it’s worth reading, but the short version is that you can use technology to “create options for policy-makers.” And working on clean energy or efficiency is definitely a […]

Read more
Machine Learning

Leveraging ANOVA and Kruskal-Wallis Tests to Analyze the Impact of the Great Recession on Housing Prices

In the world of real estate, numerous factors influence property prices. The economy, market demand, location, and even the year a property is sold can play significant roles. The years 2007 to 2009 marked a tumultuous time for the US housing market. This period, often referred to as the Great Recession, saw a drastic decline in home values, a surge in foreclosures, and widespread financial market turmoil. The impact of the recession on housing prices was profound, with many homeowners […]

Read more
Python

How to Read User Input From the Keyboard in Python

You may often want to make your Python programs more interactive by responding dynamically to input from the user. Learning how to read user input from the keyboard unlocks exciting possibilities and can make your code far more useful. The ability to gather input from the keyboard with Python allows you to build programs that can respond uniquely based on the preferences, decisions, or data provided by different users. By fetching input and assigning it to variables, your code can […]

Read more
Artificial intelligence Leave a comment

Research Focus: Week of February 19, 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. NEW RESEARCH Vertically Autoscaling Monolithic Applications with CaaSPER: Scalable Container-as-a-Service Performance Enhanced Resizing Algorithm for the Cloud Kubernetes is a prominent open-source platform for managing cloud applications, including stateful databases, which keep track of changes and transactions involving the underlying data. These monolithic applications often must rely on vertical  

Read more
Machine Learning

Garage or Not? Housing Insights Through the Chi-Squared Test for Ames, Iowa

The Chi-squared test for independence is a statistical procedure employed to assess the relationship between two categorical variables – determining whether they are associated or independent. In the dynamic realm of real estate, where a property’s visual appeal often impacts its valuation, the exploration becomes particularly intriguing. But how often do you associate a house’s external allure with functional features like a garage? Using the Ames housing dataset, this exploration delves deep into discerning whether there exists a statistically significant […]

Read more
Python

Unleashing the Power of the Console With Rich

Python’s Rich package is a versatile tool kit that enables you to generate beautifully formatted and highlighted text in the console. It extends beyond this to help you build captivating text-based user interfaces (TUIs). But why opt for a TUI instead of a graphical user interface (GUI)? There are instances where a text interface feels more fitting. Why employ a complex GUI for a simple application when an elegant text interface suffices? Working with plain text can be refreshing. It […]

Read more
Machine Learning

Testing Assumptions in Real Estate: A Dive into Hypothesis Testing with the Ames Housing Dataset

In the realm of inferential statistics, you often want to test specific hypotheses about our data. Using the Ames Housing dataset, you’ll delve deep into the concept of hypothesis testing and explore if the presence of an air conditioner affects the sale price of a house. Let’s get started. Testing Assumptions in Real Estate: A Dive into Hypothesis Testing with the Ames Housing DatasetPhoto by Alex Staudinger. Some rights reserved. Overview This post unfolds through the following segments: The Role […]

Read more
Python

Not just NVIDIA: GPU programming that runs everywhere

If you’re doing computations on a GPU, NVIDIA is the default, alongside its CUDA libraries. Some libraries like PyTorch support do support AMD GPUs and Macs. But from the re-implementations of NumPy, SciPy, and Pandas in the RAPIDS project, to Numba’s GPU support, NVIDIA has best software support in the Python world. Sticking to NVIDIA-specific software has some downsides, however: It won’t run on modern Mac laptops. Testing in CI is more difficult: you need custom runners that have NVIDIA […]

Read more
Human-computer interaction Leave a comment

What’s Your Story: Nicole Forsgren

GEHRKE: We’ve talked a little bit beforehand, but you’ve had this amazing career in tech. How did you actually … tell us a bit about how you grew up, and how did you end up in tech? NICOLE FORSGREN: Yeah, it’s, you know, it’s, kind of, this ridiculous story. I grew up in a little farm town and ended up going to college and thought I would just be there a year or two because … GEHRKE: Little farm town […]

Read more
Machine Learning

Inferential Insights: How Confidence Intervals Illuminate the Ames Real Estate Market

In the vast universe of data, it’s not always about what we can see but rather what we can infer. Confidence intervals, a cornerstone of inferential statistics, empower us to make educated guesses about a larger population based on our sample data. Using the Ames Housing dataset, let’s unravel the concept of confidence intervals and see how they can provide actionable insights into the real estate market. Let’s get started. Inferential Insights: How Confidence Intervals Illuminate the Ames Real Estate […]

Read more
1 … 55 56 57 58 59 … 908