What we're about

Welcome to Data Science Dojo's Washington DC Meetup group. Our goal is to help connect other like-minded business professionals who are interested in teaching, learning, and sharing their knowledge and understanding of data science to a larger community.

We encourage all members of this group to be pro-active in leading discussions on topics related to data science like machine learning, artificial intelligence, predictive analytics, big data, and IoT, as well as programming languages such as R, Hadoop, and Python.

Stay tuned to our Meetup calendar for future community events and be sure to follow us on Twitter at @DataScienceDojo. Also, be sure to visit our data science bootcamp ( https://datasciencedojo.com/data-science-bootcamp/ ) for more information about our training.

Upcoming events (4+)

JavaScript for Cancer Prevention through Early Detection

Link visible for attendees

Skin cancer is a serious problem worldwide but luckily treatment in the early stage can lead to recovery. JavaScript together with a machine learning model can help Medical Doctors increase the accuracy of melanoma detection. During the presentation, Karol will show how to use Tensorflow.js, Keras, and React Native to build a solution that can recognize skin moles and detect if they are melanoma or benign mole. He will also show issues that they have faced during development. In summary, the session includes the pros and cons of JavaScript used for machine learning projects.

Between the Spreadsheets: classifying and fixing dirty data for data science

Link visible for attendees

In this session, Susan Walsh will share real-life examples of dirty data, and the consequences it has on the output, such as decision making, reporting, analytics, AI, and machine learning. You’ll also learn how to make quick, accurate checks and changes to your own data in excel, regardless of your level of experience, explain why data accuracy and maintenance are so important, and implement best practices for this.

R and Python: the best of both worlds

Link visible for attendees

One of the most common data science questions is what language beginners should learn, R or Python. This has led to a rivalry between the two languages, termed the "Language War". The purpose of this talk is to announce that this rivalry is over, and we are entering a new era. We'll go through the main defining features of both languages (influenced by their history) and how they compare between different workflows in data science (i.e., data visualization, machine learning) and data types (i.e., text, image, or time series). As a final element, I'll show what methods are available for combining both in the same workspace and demonstrate this with a case study. At the end of the talk, you'll be able to appreciate why being bilingual is essential for a modern data scientist and what are the best ways to get started.

Six Business Skills Critical for Data Scientists

Link visible for attendees

This talk will introduce the foundational business skills you'll need to deliver business value and grow your career as an analyst or data scientist. Drawing on best practices, published research, case studies, and personal anecdotes from two decades of industry experience, David Stephenson will give an overview of foundational skills related to Company, Colleagues, Storytelling, Expectations, Results, and Careers--emphasizing how each topic relates to your unique position as an analytics professional within a larger corporation.

Past events (66)

Time Series Analysis with the KNIME Analytics Platform

This event has passed

Photos (51)