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March 2020

Upcoming Events
 

A Day in the Life of a Data Journalist
March 12 | 6:30 PM | Baltimore

Despite gaining prominence in recent years, “data journalism” is still a confusing term for many people. What does it mean to crunch numbers for the news? How does data journalism differ from data science and statistics, and where are the intersections? Come hear all about the world of news nerdery from your friendly neighborhood data journalist.
For more information and to register, please click here.

Past Events


Making Apache Spark Better With Delta Lake | February 2020
Video available here.

Robotics and Machine Learning: Working with NVIDIA Jetson Kits | December 2019
Video available here.

Connect Data and Devices with Apache NiFi | November 2019
Video available here.

Special Session: Introduction to Machine Learning | September 2019
Video available here.

Additional videos are available here.
 

Partner Announcements

 

Happy Hour
March 18 | 5:30 PM - 7:30 PM | The Ale House, Columbia

 
Join us for drinks and appetizers to learn more about cybersecurity and IT opportunities at ICF. ICF’s current cybersecurity, data science, software development, systems/network engineers, and cloud architecture opportunities come with great experience and exposure to cutting-edge cybersecurity tools and use of the latest emerging technology and products. If you’re a cleared IT professional and have this expertise, we would love to meet you! For questions, contact Carl Coppadge.
 

Opportunities

 
Upcoming Baltimore Hackathon
Have an idea for Baltimore Hackathon taking place in Spring 2020? Submit your idea here

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 opportunities available with our sponsors and partners.

Interested in side projects?
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?
If so, please send us an email to discuss building a side project group.

Get involved!
Want to be more involved in our data science community? If you have experience running workshops, hackathons, 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 info@eriasventures.com.
 

Data News and Articles

 

Baltimore Ravens and the NFL Analytic Revolution — The Ravens had the best regular-season record in football this season thanks to their embrace of innovative, data-driven on-field strategies.
For more, click here.

The New Business of AI (and How It's Different From Traditional Software) — Blog post from the folks at Andreessen Horowitz about how AI businesses will not resemble traditional software companies.
For more, click here.

Data Science is Boring — While real-world data science is difficult, data scientists will eventually get bored and frustrated.
For more, click here.

One Nation, Tracked — An investigation into the smartphone tracking industry by the New York Times. This multi-part article reveals what was found, discusses the security risks, and looks into the legal and ethical justifications that companies rely on to collect our precise locations and the deceptive techniques they use to lull us into sharing it.
For more, click here.

Why TinyML is a Giant Opportunity — TinyML broadly encapsulates the field of machine learning technologies capable of performing on-device analytics of sensor data at extremely low power. It is now possible to run increasingly complex deep learning models (the foundation of most modern artificial intelligence applications) directly on microcontrollers
For more, click here.
 


 

The Military Is Building Long-Range Facial Recognition That Works in the Dark — The U.S. military is spending more than $4.5 million to develop facial recognition technology that reads the pattern of heat being emitted by faces in order to identify specific people. The technology would work in the dark and across long distances, according to contracts posted on a federal spending database.
For more, click here.

A Decade in Review in Tech — Typed languages, SQL, streaming and continuous integration are some of the key technological adoptions in the past decade.
For more, click here.

5 Key Areas for Tech Leaders to Watch in 2020 — O’Reilly annual analysis reveals Python’s continued dominance and important shifts in infrastructure, AI/ML, cloud, and security.
For more, click here.

Navigating Without a Map — A team at Facebook AI has created a reinforcement learning algorithm that lets a robot find its way in an unfamiliar environment without using a map. Using just a depth-sensing camera, GPS, and compass data, the algorithm gets a robot to its goal 99.9% of the time along a route that is very close to the shortest possible path, which means no wrong turns, no backtracking, and no exploration. This is a big improvement over previous best efforts.
For more, click here.

How-To's and Tutorials

 

 
Interactive Data Visualization in Python With Bokeh — Bokeh prides itself on being a library for interactive data visualization. Unlike popular counterparts in the Python visualization space, like Matplotlib and Seaborn, Bokeh renders its graphics using HTML and JavaScript. This makes it a great candidate for building web-based dashboards and applications. However, it’s an equally powerful tool for exploring and understanding your data or creating beautiful custom charts for a project or report.
For more information, click here.

Apache Icberg — Apache Iceberg is an open table format for huge analytic datasets. Iceberg adds tables to Presto and Spark that use a high-performance format that works just like a SQL table.
For more information, click here.

Materialize: the Streaming Data Warehouse — Materialize lets you ask questions of your live data, which it answers and then maintains for you as your data continue to change. The moment you need a refreshed answer, you can get it in milliseconds. Materialize is designed to help you interactively explore your streaming data, perform data warehousing analytics against live relational data, or just increase the freshness and reduce the load of your dashboard and monitoring tasks.
For more information, click here and here.

Five Interesting Data Engineering Projects — DBT (Data Build Tool), Perfect, Dask, DVC, and Great Expectations are five great projects that data engineers should keep up with.
For more information, click here.
 

Data Tools and Resources

 
The Big List of Data Science Interview Resources — Data science interviews aren’t easy. This extensive list covers everything you need to ace a data science interview.
For more information, click here.

30 Python Best Practices, Tips, And Tricks — Here are 30 Python best practices, tips, and tricks. I’m sure they’ll help you procrastinate your actual work, and still learn something useful in the process.
For more information, click here.

Time Series Prediction - A Short Introduction for Pragmatists — Are you trying to predict time series but don't know where to start? This blog post will provide a comparison of the most prominent techniques and show you how to implement them.
For more information, click here.

An Introduction to Confident Learning: Finding and Learning with Label Errors in Datasets This post discusses an emerging, principled framework to identify label errors, characterize label noise, and learn with noisy labels known as confident learning (CL), open-sourced as the cleanlab Python package.
For more information, click here.
 
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If you are interested in speaking, hosting, or sponsoring a meetup, have opportunities to list, or local news to share, please email info@dataworksmd.org.






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