ISSUE 393  ·   June 28, 2022

Trends

The evolution of machine learning infrastructure

Budgets for data and machine learning are hitting all-time highs and lots of value is being created across the space. In this post from Bessemer Venture Partners, Bhavik Nagda and Sakib Dadi explore what’s been happening in the machine learning technology stack, the key trends driving innovation, and where the opportunities are now.
Bessemer Venture Partners | Atlas

Fair Game

Web scraping is widely used by industry and researchers and has been deemed to be legal by courts in the U.S. Even so, using scraped data in contexts that it wasn't intended is rife with problems. This is a great article about the complicated dance between privacy, research, and the industries that have evolved around scraped data.
Real Life | David Golumbia

Sponsored Link

How to Capture Advantages by Investing in High-Quality Training Data

At the enterprise level, machine learning requires either large amounts of training data or a smaller set of extremely high quality data, as well as the infrastructure to support high data volumes. Consequently, labeling data through robust software or in partnership with an annotation service provider is critical to project success. Read more.

Tutorials, Projects & Opinions

Things You Should Know About Databases

It's surprisingly easy to work with databases and not really understand basic principles about how they work. In this primer, Mahdi Yusuf walks through two of the most important topics when working with relational database systems: indexes and transactions.
Architecture Notes | Mahdi Yusuf

One year as a solo dev building open-source data tools without funding

Great, first-hand account of turning a side project into something big. Or, bigger, anyway. The reality is, going solo is complicated but, in spite of that, there's been a lot of interest in Phil Eaton's DataStation recently. This post covers the journey so far: from problem definition to software development to VC interest, and 4000 stars on GitHub!
Phil Eaton

Why I still recommend Julia

A few weeks ago, there were lengthy online discussions about bugs in the Julia ecosystem and why it shouldn't be used when correctness matters. In this counter-post, Rik Huijzer walks through the things that Julia gets right and why, even though Julia isn't perfect, he still recommends it. Includes links to key discussions.
Rik Huijzer

OpenBB Terminal 

OpenBB Terminal is an open-source, Python-based platform for investment research. It's inspired by Bloomberg Terminal but without the fees. It gives you access to massive amounts of real-time and historical data and since it's Python, you can use common data science libraries with it like Pandas, Numpy, Scipy, Jupyter, Pytorch, etc.
OpenBB-finance

Data Product in Changing Environments: Rethinking and Updating Investments

Datasets and tools that are built for specific people in an organization can easily be forgotten when those people leave. If you're the one building those tools, here's a better way to approach new projects to make sure your time is well spent.
From Data to Product | Eric Weber

Top 3 ways IMDb’s third-party data enhances user engagement and experience

Join this virtual event to learn the top 3 ways to increase customer engagement and improve user experience by leveraging IMDb’s third-party data. Speakers from AWS and IMDb will show you how to gain new consumer insights, deploy customer-centric features, and create personalized user experiences. Register Now
// sponsored

Career

Workforce Wanted - Data Talent For Social Impact

This new report explores the rapidly growing landscape of data for social good. The report is primarily focused on ways to develop a global talent force of purpose-driven data professionals and along the way, it highlights issues and opportunities.
data dot org

Data Visualization

Hard Data: The Erotics Of Infographics

This is an edgy take on infographics but it sure is compelling: at the end of the day, much of the media's interest in data lies in its monetization. And it turns out, visualization and the data fetishism that the media has fostered with it has created an easy way to convert data to dollars.
Gawker | Ben Lee

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