Data Works MD Conference 2021
We are in the early planning stages for a Maryland data-focused conference in June 2021. If you would like to stay informed, please sign-up for updates
Interested in a side project?
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.
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 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 email@example.com
Data News and Articles
Facebook’s ‘Red Team’ Hacks Its Own AI Programs — Facebook depends heavily on moderation powered by artificial intelligence, and it says the tech is particularly good at spotting explicit content, but it becomes a cat-and-mouse game. This prompted Facebook a few months later to create an “AI red team” to better understand the vulnerabilities and blind spots of its AI systems. Other large companies and organizations, including Microsoft and government contractors, are assembling similar teams. Tags: AI
Hiding In Plain Sight: Deep Steganography — Can we design a neural network to find a full-sized color image hidden inside another image? How might changing learning rates and other hyperparameters affect our model performance? Tags: Deep Learning
Lawmakers Want More AI for Military — The Defense Department has identified microelectronics, 5G communications, and hypersonics as its top three research-and-development priorities but others think that AI should be the top priority. Tags: AI, Defense
6 Lessons Learned to Get Ready for the Next Wave of COVID — This article covers a number of lessons including establishing a foundation for a data-driven public health system, mobile apps won’t save the day, but can be a powerful asset, and why modeling is hard. Tags: Data, COVID-19
How Duolingo Uses AI in Every Part of Its App — This is article discusses the AI behind Stories, Smart Tips, podcasts, reports, and even notifications in the Duolingo app. Tags: AI
Time to Build Robots for Humans, Not to Replace — Thinking about the future of robots and autonomy is exciting; driverless cars, lights-out factories, urban air mobility, robotic surgeons available anywhere in the world. We’ve seen the building blocks come together in warehouses, retail stores, farms, and on the roads. It is now time to build robots for humans, not to replace them. Tags: Robots
The Rise of DataOps — Companies know they need data governance, but aren’t making any progress in achieving it. These days, executives are interested in data governance but the vast majority of data governance initiatives fail to move the needle. Tags: Data
Why Uber Engineering Switched from Postgres to MySQL — The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. This article discusses some of the drawbacks we found with Postgres and explains the decision to build Schemaless and other backend services on top of MySQL. Tags: Data, SQL
Data Science: Why Humans Are Just as Important as Math — It's not easy to teach machines how to apply a critical lens to data. Businesses need human intuition and creativity for multi-faceted problems. Tags: Data Science
Deep Learning's Most Important Ideas - A Brief Historical Review — The goal of this post is to review well-adopted ideas that have stood the test of time. I will present a small set of techniques that cover a lot of basic knowledge necessary to understand modern Deep Learning research. If you're new to the field, these are a great starting point. Tags: Deep Learning
How-To's and Tutorials
Spinning Up in Deep RL — Reinforcement learning
(RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning
. This education resource makes it easier to learn about deep RL with a short introduction, curated list of papers, sample code repository, and exercises. Tags: Deep Learning
Machine Learning from Scratch —
A free book that covers the building blocks of the most common methods in machine learning. This set of methods is like a toolbox for machine learning engineers. Those entering the field of machine learning should feel comfortable with this toolbox so they have the right tool for a variety of tasks. Each chapter in this book corresponds to a single machine learning method or group of methods. In other words, each chapter focuses on a single tool within the ML toolbox. Tags: Machine Learning
Data Tools and Resources
Dagster: The Data Orchestrator — Dagster is a new type of workflow engine: a data orchestrator. Moving beyond just managing the ordering and physical execution of data computations, Dagster introduces a new primitive: a data-aware, typed, self-describing, logical orchestration graph. This graph explicitly models an implicit, pre-existing structure in every data application and platform. We believe this graph is integral to the entire application lifecycle and, when made accessible and operable over an API, can form the basis of an entire ecosystem of tools and libraries. Tags: Tools, Data
FAST — FAST is a collection of technologies built on Web Components and modern Web Standards, designed to help you efficiently tackle some of the most common challenges in website and application design and development. Tags: Tools, Web
Elyra is a set of AI-centric extensions to JupyterLab Notebooks including notebook pipeline visual editor, running notebooks as batch jobs, and notebook versioning. Tags: Tools, Notebooks
An ergonomic machine learning library for non-technical users. Save time. Blaze through ML. Tags: Tools, Machine Learning
fast.ai is a self-funded research, software development, and teaching lab, focused on making deep learning more accessible. They recently released fastai v2
, several foundational libraries, a new book
, the Practical Deep Learning for Coders
course. Tags: Tools, Machine Learning