Scaling Python: The Banking Edition
In this post, we walk you through how Quansight helped a banking client through the process of scaling Python DataFrame calculations in a real-life scenario.
Pandas and the Geosciences: A 4.5 Billion Year Story
How Quansight and the University of Southern California joined forces to make Pandas available for use in the paleogeosciences by implementing a community-requested feature dating back to 2014.
Exploring the Impact of Feedback Loops on LLM Code Generation
Overview Large Language Models (LLMs) have been around for several years but recent advances have revolutionized the field of natural language processing (NLP) and artificial intelligence (AI), opening up a world of possibilities across various domains. OpenAI’s ChatGPT has taken the world by storm and shown remarkable ability to generate human-like responses to a wide range of […]
A Year in Review: Quansight’s Contributions to PyTorch in 2022
2022 was an exciting year for the PyTorch ecosystem. The PyTorch project joining the Linux Foundation was a major milestone, and PyTorch 2.0 was announced with loads of informative talks from the maintainers explaining new features. Additionally, there was marked progress on areas including sparse tensors, JAX-like transformations in PyTorch were released, and TorchVision announced a new Transforms API. In this post, we will […]
Evolving QHub to Nebari: Your Open Source Data Science Platform
Co-authors: Tania Allard, Brian Skinn, Dharhas Pothina We’re excited to announce a new chapter for Nebari, formerly known as QHub, as it evolves into an independent, community-led project, with a fresh new look! Since its launch nearly two years ago, Quansight has been incubating and developing Nebari—a fully open source collaboration platform for data science and […]
Dash, Voila, Panel, & Streamlit—Our Thoughts on the Big Four Dashboarding Tools
At Quansight, we use the top four Python dashboarding tools and clients often ask which one we recommend. Here’s our breakdown of each and why you might choose one over another. The Power of Interactive Data Visualization TLDR: There are many great interactive dashboarding options in Python, which should you use? Jump to the comparison […]
A Year in Review: Quansight’s Contributions to PyTorch in 2021
Co-author: Mario Lezcano PyTorch is a very popular open source deep learning framework, primarily developed by Meta AI. If you are making deep learning models, chances are you are using PyTorch. Not only is Quansight a major contributor to the development of PyTorch, but we also use it in applied data science consulting projects as […]
Exploring Reinforcement Learning
Reinforcement learning, a type of machine learning, can tackle a wide range of complex issues. Some of the applications include autonomous driving, robotics, trading strategies, healthcare treatment policy, warehouse management, strategic game theory, and many others. The list goes on long enough that one might be tempted to see the technology as magic. If you […]
Up and Running With Prefect
Note: This post discusses the 1.x version of Prefect, and not the newer 2.x series. There are many types of computations that can be broken down into subtasks. Some of these tasks may be resource-intensive or long-running, and may fail at any time for multiple reasons. Being able to define tasks, chain them together, and […]
Acceleration in Python: Which Is Right for Your Project?
Quansight recently assisted the University of Oxford on the sgkit library, a new genetics toolkit. Sgkit is based on the scikit-allel project, which has moved into maintenance mode. Part of the impetus behind this large rewrite was to (1) allow for larger genomics datasets, (2) enable GPU support, and (3) transition to a more sustainable, community-maintained project. Sgkit is […]
