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 […]

February 15, 2024 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 […]

February 15, 2024 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 […]

February 15, 2024 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 […]

February 14, 2024 Python

BNF Notation: Dive Deeper Into Python’s Grammar

While reading the Python documentation, you may have found fragments of BNF notation (Backus–Naur form) that look something like the following: What’s the meaning of all this strange code? How can this help you in understanding Python concepts? How can you read and interpret this notation? In this tutorial, you’ll get to know the basics of Python’s BNF notation and learn how to take advantage of it to get a deep understanding of the language’s syntax and grammar. To get […]

February 13, 2024 Artificial intelligence Leave a comment

GraphRAG: Unlocking LLM discovery on narrative private data

Perhaps the greatest challenge – and opportunity – of LLMs is extending their powerful capabilities to solve problems beyond the data on which they have been trained, and to achieve comparable results with data the LLM has never seen. This opens new possibilities in data investigation, such as identifying themes and semantic concepts with context and grounding on datasets. In this post, we introduce GraphRAG, created by Microsoft Research, as a significant advance in enhancing the capability of LLMs. Retrieval-Augmented […]

February 13, 2024 Python

Create Conway’s Game of Life With Python

Wouldn’t it be cool to build a Python game that only requires initial user input and then seems to take on a mind of its own, creating mesmerizing patterns along the way? You can do exactly that with Conway’s Game of Life, which is about the evolution of cells in a life grid. Implementing the Game of Life algorithm is a good exercise with many interesting challenges that you’ll have to figure out. Specifically, you’ll need to build the life […]

February 12, 2024 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 […]

February 9, 2024 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 […]

February 9, 2024 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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