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Data Works MD consists of professionals, students, and enthusiasts living and working in the Maryland area that are interested in topics related to data science, data analytics, data products, software engineering, machine learning, and other data engineering topics.

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Register for one of our upcoming events!


Recent videos of our events can be found below. More are available at YouTube.

March 20, 2021

Data Science Product Management

When put into service solving customer needs, data science can be a critical differentiator for digital products in ever-more-competitive markets. But productizing data science presents a unique set of challenges, and often leaves product managers and data scientists struggling to find common ground and a shared language. In this talk, product coach and consultant Matt LeMay shares the lessons he's learned building bridges between product management and data science at companies like Bitly, Songza, and Spotify. Expect a candid, direct, and entertaining conversation about mistakes made, lessons learned, and suggestions for how to move forward.


February 24, 2021

ML Design Patterns and Designing ML Infrastructure

Design patterns are formalized best practices to solve common problems when designing a software system. As machine learning moves from being a research discipline to a software one, it is useful to catalog tried-and-proven methods to help engineers tackle frequently occurring problems that crop up during the ML process. In this talk, I will cover five patterns (Workflow Pipelines, Transform, Multimodal Input, Feature Store, Cascade) that are useful in the context of adding flexibility, resilience and reproducibility to ML in production. For data scientists and ML engineers, these patterns provide a way to apply hard-won knowledge from hundreds of ML experts to your own projects.


January 16, 2021

Malware Detection, Enabled by Machine Learning

With the scale of new malware being created each year growing, as well as the expanding market opportunities for malware reuse, protecting systems can’t rely solely on downloading a vendor’s updated virus signature files. Our customers need ways to detect and cordon likely threats, by using data retrieved from a combination of static and behavioral characteristics, and comparing it to other classes of “good” versus “bad” files. Optimally, the solution cordons risky files, force ranks them according to their likelihood of causing harm, correlates some metadata to help with further learning and to provide context to analysts, and lets an analyst “release” a file after further analysis and a request from a user. Oh, with that feedback relayed back into the model to support further tuning.


Novenber 7, 2020

Edge Device Computing for Machine and Deep Learning

Edge computing is a distributed computing model in which computing takes place near the physical location where data is being collected and analyzed, rather than on a centralized server or in the cloud. According to Gartner "91% of today’s data is created and processed in centralized data centers. By 2022 about 75% of all data will need analysis and action at the edge."


October 6, 2020

Wrangling Data and Visualizing Patterns with Python and GIS

A geographic information system (GIS) is a framework for gathering, managing, and analyzing data. Rooted in the science of geography, GIS integrates many types of data. GIS data is used for a variety of purposes including mapping, urban planning, agriculture, and banking. Join us in October to learn how you can use Python to explore, analyze, and work with GIS data.


Interesting articles, tools, and tutorials. More are available at our newsletter archive.

Data Works MD May 2021 Issue

Product teams, defensible ML, time series forecasting, DAX...

Data Works MD April 2021 Issue

ML in game development, graphing COVID, Pokemon or Big Data, ...

Data Works MD March 2021 Issue

Gender equality in AI, Julia as a replacement for Python, a framework for easier documentation, ...


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