Starburst Introduces Python DataFrame Support for Complex Data Transformation and Data Application Workloads

Starburst, the data lake analytics platform, today extended their support for the most widely used multi-purpose, high-level programming language, Python with PyStarburst, as well as announced a new integration with the open source Python library, Ibis, built in collaboration with composable data systems builder and Ibis maintainer, Voltron Data. 

UMass Amherst Computer Scientists Use AI to Accelerate Computing Speed by Thousands of Times  

A team of computer scientists at the University of Massachusetts Amherst, led by Emery Berger, recently unveiled a prize-winning Python profiler called Scalene. Programs written with Python are notoriously slow—up to 60,000 times slower than code written in other programming languages—and Scalene works to efficiently identify exactly where Python is lagging, allowing programmers to troubleshoot and streamline their code for higher performance.

Anaconda Distribution for Python Brings Data Science to Hundreds of Millions of Microsoft Excel Users

Anaconda Inc., the provider of one of the world’s most widely used and trusted data science and AI platforms, announced the beta availability of Anaconda Distribution for Python in Excel, a new integration with Microsoft Excel.  Anaconda’s Python distribution is fully embedded and integrated into the Excel grid toolboxes for manipulating, analyzing, and visualizing data and for advanced machine learning and AI. Python in Excel is currently rolling out to Public Preview and is available for Microsoft Insiders.

Lightning AI Releases PyTorch Lightning 2.0 and a New Open Source Library for Lightweight Scaling of Machine Learning Models 

Lightning AI, the company accelerating the development of an AI-powered world, today announced the general availability of PyTorch Lightning 2.0, the company’s flagship open source AI framework used by more than 10,000 organizations to quickly and cost-efficiently train and scale machine learning models. The new release introduces a stable API, offers a host of powerful features with a smaller footprint, and is easier to read and debug.

Video Highlights: Distributed Python with Ray

This is an introductory and hands-on guided tutorial of Ray2.0 that covers an introductory, hands-on coding tour through the core features of Ray, which provides powerful yet easy-to-use design patterns for implementing distributed systems in Python.

The Anyscale Platform™, built on Ray, Introduces New Breakthroughs in AI Development, Experimentation and AI Scaling

Anyscale, the company behind Ray open source, the unified compute framework for scaling any machine learning or Python workload, announced several new advancements on the Anyscale Platform™ at AWS re:Invent in Las Vegas, NV. The new capabilities extend beyond the advantages of Ray open source to make AI/ML and Python workload development, experimentation, and scaling even easier for developers.

Anaconda Announces Collaboration with Esri, Setting the Enterprise Standard for Python Across the Geospatial Community

Anaconda Inc., provider of the popular data science platform, announced a collaboration with Esri, the global market leader in geographic information system (GIS) software, location intelligence, and mapping. This collaboration supports Esri and the geospatial community by providing users of Esri’s software with preloaded geospatial packages for use with Python.

Python Madness

The Python MVP March Madness 2022 tournament also has arrived at its championship game, with echoes of the real NCAA. Two weeks ago, the tournament began with 32 Python packages matched up in a head-to-head, lose-or-go-home tournament play. The community voted, round-by-round, and delivered NumPy and pandas to the final game.

Video Highlights: A Path Into Data Science

Are you interested in getting ahead in data science? On this TalkPython podcast episode, you’ll meet Sanyam Bhutani who studied computer science but found his education didn’t prepare him for getting a data science-focused job. That’s where he started his own path of self-education and advancement. Now he’s working at an AI startup and ranking high on Kaggle.

Video Highlights: Thinking Sparse and Dense

The video below, “Thinking Sparse and Dense” is the presentation by Paco Nathan from live@Manning Developer Productivity Conference, June 15, 2021. In a Post-Moore’s Law world, how do data science and data engineering need to change? This talk presents design patterns for idiomatic programming in Python so that hardware can optimize machine learning workflows.