March 2021

Upcoming Events


Pitch! - Yourself, Your Company, Your Project, Your Ideas!

Presented by YOU!
May 8 | 1:00 PM | Online

Looking for a job? Looking to hire someone? Trying to get your project started? Grab your best pitch and come share with the Data Works MD community. We need speakers! If you would like to speak, please register here.



What are you interested in?

Have something you're wondering about? Would you like to learn more about a topic? Reach out and let us know. We would be paw-sitively delighted to find a speaker.

Past Events

We hope you caught the brilliant talk by Dr. John Piorkowski on the role of data during apocalyptic times.  If you missed it, you can find it, and many other fantastic presentations, on our YouTube channel.
Don't forget to subscribe so you don't miss a thing! 



DAX 2021
We are in the early planning stages for a Maryland data-focused conference in 2021. If you would like to stay informed, please sign-up for updates.

Be a Do-Gooder
Are you looking for a way to get involved in the community and make an impact? Check out the volunteer opportunities with U.S. Digital Response.  

Book Review Opportunity
Are you interested in reviewing an O'Reilly book for the publisher and sharing your views with the world? As if that isn't enough, you get to take a book home to enjoy as well. Send us an email and we'll get you started.

Data Analysis Volunteer Work to Support Baltimore City
Are you an expert with data and willing to mentor, or are you an up and coming hobbyist looking for a side project to work on? We have put together a group to focus on a few problems working with Baltimore City data and need your help. The current project focuses on data parsing and analysis for the Baltimore Board of Estimates. If interested, please send us an email or join us on Slack to discuss building a side project group.

Considering a Career Change?
Are you a software or system engineer, data scientist, analytic developer, or cybersecurity expert interested in learning about new opportunities?
Please send us an email to learn about the opportunities available with our partners.

Are You Hiring?
If your company is looking for data scientists, data engineers, software engineers, and other data related experts, please reach out so that we can help our members find new opportunities.
Please send us an email introducing your company and needs.

Get Involved with Data Works!
Want to be more involved in our data science community? If you have experience running workshops, hack-a-thons, curating newsletters, or are just interested in helping to grow the meetup, please send us an email!

Erias Ventures
Erias has an immediate need for Software Engineers, System Engineers, Test Engineers, Data Scientists, and System Administrators. External referral bonuses are available. For more information, please contact us at

Data News and Articles


Introducing the MAD (ML, AI, Data) Public Company Index – Matt Turuk previews a new public market index – the MAD (for machine learning, AI and data) index. Tags: AI, Money, Market, ML

Facebook’s Next Big AI Project Is Training Its Machines on Users’ Videos – Teaching AI systems to understand what’s happening in videos as completely as a human can is one of the hardest challenges — and biggest potential breakthroughs — in the world of machine learning. Today, Facebook announced a new initiative that it hopes will give it an edge in this consequential work: training its AI on Facebook users’ public videos. Tags: AI, Facebook

Lessons from a Year of Contributing to Open Source - Niall Rees Woodward – A year ago I decided a top priority for 2020 was finding an open source project to contribute to. In this post I reflect on my experience, what I wish I’d known before I started, and to what extent my initial expectations held true. Tags: Open Source 

 – This article discusses the use of machine learning (ML) to adjust game balance by training models to serve as play-testers, and demonstrate this approach on the digital card game prototype Chimera, which we’ve previously shown as a testbed for ML-generated art. Tags: ML, Gaming

GPT-3 Powers the Next Generation of Apps – Nine months since the launch of our first commercial product, the OpenAI API, more than 300 applications are now using GPT-3, and tens of thousands of developers around the globe are building on our platform. We currently generate an average of 4.5 billion words per day, and continue to scale production traffic. Tags: app, platform, Viable

Uber's Journey Toward Better Data Culture from First Principles – Uber has revolutionized how the world moves by powering billions of rides and deliveries connecting millions of riders, businesses, restaurants, drivers, and couriers. At the heart of this massive transportation platform is Big Data and Data Science that powers everything that Uber does, such as better pricing and matching, fraud detection, lowering ETAs, and experimentation. Petabytes of data are collected and processed per day and thousands of users derive insights and make decisions from this data to build/improve these products. Tags: Uber, Big Data, Data Analysis

Synthetic Data: Sometimes Better Than the Real Thing – Having a large stockpile of data is still a prerequisite for advanced analytics and AI. But companies building AI models increasingly are finding that artificially created data can be just as good as the real thing. And in some cases, synthetic data is a superior alternative, specifically when it comes to issues of bias and ethics. Tags: Data, bias, AI

Graphing the Pandemic – 2020 was literally off the charts. Data journalists saw changes that typically take months instead happening in weeks — numbers that will be breaking the y-axis for years to come. Tags: Pandemic, Data Visualization

How We Built a Context-Specific Bidding System for Etsy Ads – Etsy Ads is developing a neural-network-powered platform that can determine, at request time, when the system should bid higher or lower on a seller’s behalf to promote their item to a buyer. We call it contextual bidding, and it represents a significant improvement in the flexibility and effectiveness of the automation in Etsy Ads. Tags: Predictive Analysis, Etsy

Data Scientists Are Predicting Sports Injuries with an Algorithm – Athletes and parents of athletes take note! Machine learning can tell athletes when to train and when to stop. Tags: ML, Medical Prevention

An Artificial Intelligence Tool That Can Help Detect Melanoma – Using deep convolutional neural networks, researchers devise a system that quickly analyzes wide-field images of patients’ skin in order to more efficiently detect cancer. Tags: AI, Medical Prevention, Neural Networks

The Cult of CryptoPunks – Ethereum's 'oldest NFT project' may not actually be the first, but it's the wildest. Tags: NFT, CryptoCurrency

The Ghosts in the Data – The basic block of labor of machine learning is cleaning data and setting up engineering pipelines, the detailed and tedious work of making all the pieces fit together. Tags: ML, Data, Models

A View of The Future of Our Data – In this essay, addressed to the reader from 2022, I will depict and defend an attractive, feasible vision for the future of the data economy. But make no mistake: We’re going to have to fight for it. Tags: Data Coalition

Why the Pandemic Experts Failed – We’re still thinking about pandemic data in the wrong ways. For months, the American government had no idea how many people were sick with COVID-19, how many were lying in hospitals, or how many had died. And the COVID Tracking Project at The Atlantic, started as a temporary volunteer effort, had become a de facto source of pandemic data for the United States. Tags: Data, COVID, Pandemic

The Foundations of AI Are Riddled With Errors – Deep learning, which involves feeding examples to a giant simulated neural network, proved dramatically better at identifying objects in images than other approaches. That kick-started interest in using AI to solve different problems. But research revealed this week shows that ImageNet and nine other key AI data sets contain many errors. Tags: AI, deep learning, ImageNet, Data

How-To's and Tutorials

One Question To Make Your Data Project 10x More Valuable – Data folks are in the business of helping people make decisions. Whether it's a quick and dirty ad-hoc query or a super sophisticated statistical model, at the end of the day we're informing a decision. Tags: Data Collection

Get Better at Programming by Learning How Things Work – 
When we talk about getting better at programming, we often talk about testing, writing reusable code, design patterns, and readability. All of those things are important. But in this blog post, I want to talk about a different way to get better at programming: learning how the systems you’re using work!
Tags: Programming, how to

The Architecture Behind A One-Person Tech Startup – This is a long-form post breaking down the setup I use to run a SaaS. From load balancing to cron job monitoring to payments and subscriptions. There's a lot of ground to cover, so buckle up! Tags: SaaS, StartUp, Kubernetes, AWS, Django, Rails

Building Powerful Data Teams: On Investing in Junior Talent – I want to share a sort of step-by-step recounting of how I built a culture of learning and growth on my data team and spent a year investing in junior talent. My hope is that other managers adopt a similar attitude for their data teams, and that you also can share with me what you have done for your teams! Tags: Management, Retention, Recruiting

Progressively Approaching Kaggle – The Titanic Competition is most people’s first attempt at getting started on Kaggle. It has a wonderful archive of resources but if you’re looking for something newer, quicker and progressive that gets you acquainted with Kaggle competitions, then the Tabular Playground Series is a fantastic place to start. Tags: Kaggle, TPS

Data Tools and Resources

Is It a Pokémon or a BigData Tech? – Take a break from the stresses of the day and test your knowledge of Pokémon or BigData tech stacks. How many will you get right? Tags: Pokémon, Tech Stack

Understanding front-end data visualization tools ecosystem in 2021 –  In this post we're going to go through JavaScript frameworks and libraries that you can use to visualize your data. Tags: JavaScript

Ploomber – Ploomber is a Python package for building data pipelines for data science and machine learning. In a given pipeline, tasks can be anything from Python functions, notebooks, Python/R/Shell scripts, and SQL scripts. Tags: Python, SQL

My Love / Hate Relationship With Jupyter – Why Jupyter delights Data Scientists and terrifies Machine Learning Engineers. Tags: Jypter, Julia, ML

GitHub - encoredev/encore – The Go backend framework with superpowers: Encore is a Go backend framework for rapidly creating APIs and distributed systems. It uses static analysis and code generation to reduce the boilerplate you have to write, resulting in an extremely productive developer experience. Tags: API, Framework

GitHub - elixir-nx/livebook – Livebook is a web application for writing interactive and collaborative code notebooks. The notebookJS API is very simple. Actually, a single function takes care of everything: the execute_js method executes a JavaScript function and sets up the infrastructure for bidirectional communication between Python and JavaScript using callbacks. Tags: Webapp, Notebooks, Python, JavaScript


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