f Loading...
Data Works MD Logo

About Us

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.

0+ Members
0+ Events
0+ Newsletters

Upcoming

Register for one of our upcoming events!

Videos

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

Event

September 22, 2021

Idiomatic Pandas

Pandas can be tricky, and there is a lot of bad advice floating around. This talk will cut through some of the biggest issues I've seen with Pandas code after working with the library for a while and writing two books on it.

Event

August 27, 2021

Estimating Lottery Revenue on a Quantum Computer

Learning quantum computing can be daunting due to the need to learn matrix algebra and probabilities. However, that doesn’t have to be the case. You can solve existing business problems with just college algebra and python. This presentation will show how an optimization problem can be set up on a quantum computer. The business problem is based on a state lottery trying to minimize sales (consumer taxes) in specific locations, while maximizing state-wide total revenue. This presentation offers a first-step approach to learning quantum computing by walking through code that runs on a D-Wave adiabatic quantum machine.

Event

July 24, 2021

Introducing Datawave - Scalable Data Ingest and Query

In this talk, we introduce Datawave, a complete ingest, query, and analytic framework for Accumulo. Datawave, recently open-sourced by the National Security Agency, capitalizes on Accumulo's capabilities, provides an API for working with structured and unstructured data, and boasts a robust, flexible, and scalable backend. We'll do a deep dive into Datawave's project layout, table structures, and APIs in addition to demonstrating the Datawave quickstart—a tool that makes it incredibly easy to hit the ground running with Accumulo and Datawave without having to develop a complete application.

Event

June 17, 2021

Graph Analytics - Rich Relationships and Powerful Insights

Demo-Driven exploration of graph analytics to identify criminals, discover trolls, analyze social networks, and more using community detection, centrality, link prediction, and graph embedding for incorporation into machine learning models, along with creating graphs from Wikipedia via wikidata. Includes all you need to get started and a review and use of two graph query languages – cypher and SPARQL across multiple environments including Neo4J, Amazon Neptune, and Nvidia Cuda graphs for large scale graph processing using GPUs. Relationships are what it is all about

Event

April 17, 2021

The Role of Data During Apocalyptic Times

The COVID-19 pandemic is the most profound health crisis to impact the United States and the world in the past 100 years. One critical challenge since the beginning of the pandemic included accurate models to inform organizations’ responses. Numerous models and analytics emerged to address disease spread, hospital utilization, PPE demand and allocation, vaccine allocation, and mortality. Underlying these models and analytics’ efficacy is the need for quality data that provides a high degree of trust. This talk will describe our experiences at the Johns Hopkins University/ Applied Physics Laboratory since the beginning of the COVID-19 pandemic in curating and building high-quality data pipelines to inform the global response.

Event

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.

Newsletter

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

Data Works MD August 2021 Issue

AI in business, real estate, unicorns, ...

Data Works MD July 2021 Issue

Data mesh, careers in deep learning, and acing your next data science interview...

Data Works MD June 2021 Issue

DataOps, data platforms, best practices for Docker, ...

Partners

We are proudly supported by the following organizations.