What we're about

ODSC brings together the open-source and data science communities with the goal of helping its members learn, connect and grow.

The focus of this Meetup group is to allow ODSC to work with Meetup groups, non-profits, and other organizations to present informative lectures, workshops, code sprints and networking events to help grow the use of open source languages and tools within the data science and data-centric community. As such, our specific goals are:

1. Build a collaborative group to work with other Meetup groups, non-profits, and other organizations.

2. Promote the use of open source languages and tools amongst data scientists and others.

3. Host educational workshops.

4. Spread awareness of new open source languages and tools that can be used in data science.

5. Contribute back to the open-source community.

Who is this meetup for?

• Data engineers, analysts, scientists, and other practitioners

• R, Python and other software engineers who work with data or want to learn

• Data visualization developers and designers

• Non-technical team leads, executives, and other decision-makers from data-centric startups and large companies looking to utilize open-source tools

Get Involved with our Meetups:

• Speaker Form ( https://docs.google.com/a/odsc.com/forms/d/1trkCoecAMa8za_ZzfN5bW6ZNBaRlmqJSQvuME_2nbJA/edit?usp=drive_web ) - Submit a talk, tutorial, or panel.

• Suggest a Meetup Topic Form ( https://docs.google.com/forms/d/1rEjO3UMMXRXtY8Yr_J_jj3ebYwsIFqcGA6FZzWK4rd0/edit )

• Volunteer Form ( https://docs.google.com/forms/d/1Vu3B72avz2I1xx618pEFGsuywZE9t4n78br9vSEX9oE/edit )

• Host or Sponsor Form ( https://docs.google.com/forms/d/1eyM9hJ3l8TlNmw35re65mH7mFCmsPoRZ1p5RJQEVhnk/edit )

• Showcase your Startup Form ( https://docs.google.com/forms/d/1oz8A4fbfe6HHs71v4nMpcf9FP_kpS9CcCfd3qIBS5HU/edit )

Get free access to more talks like this at LearnAI

· LearnAI: https://learnai.odsc.com/

· Facebook: https://www.facebook.com/OPENDATASCI/

· Twitter: https://twitter.com/odsc & @odsc (https://twitter.com/odsc)

· LinkedIn: https://www.linkedin.com/company/open-data-science/

· Slack Channel: http://bit.ly/2RkOf9l

Upcoming events (1)

Webinar: "Azure Machine Learning Notebooks and Experimentation User Interface"

To access this webinar, please register here: https://aiplus.odsc.com/courses/azure-machine-learning-notebooks-and-experimentation-user-interface Topic: Azure Machine Learning Notebooks and Experimentation User Interface Speaker#1: Abe Omorogbe, Program Manager at Microsoft https://www.linkedin.com/in/abeomor/ Abe Omorogbe - He is a Program Manager at Microsoft. He works within the AI Platform Group specifically on Azure Machine Learning - building exciting Machine Learning tools that make Data Scientist and ML Engineers more productive. Speaker#2: Shané Winner, Program Manager at Microsoft https://www.linkedin.com/in/shan%C3%A9-winner-0aab47117/ Shané Winner – She is a Program Manager at Microsoft on the Azure Machine Learning platform team focused on improving the user experience and productivity for Data Scientists doing Machine Learning. Abstract: The enhanced notebook editor in the Azure Machine Learning Studio enables members of Azure ML workspace to edit, share and collaborate on the notebooks in the same environment that contains their ML experiments, metrics, models, datasets, and more. With the new Studio Notebooks, Data Scientists are one link away from collaboration. We believe this simplicity of sharing will be especially welcome in today’s world of mandatory remote work. The new notebook editor is based on an open-source interact project and provides full compatibility with standard Jupyter. The editor also brings some best-in-class code editor features from VS Code that our customers know and love. For the first time, Data Scientists can use advanced features like full IntelliSense and inline error highlighting directly in their Jupyter notebooks. The Experiments UI in the Azure Machine Learning Studio enables users to inspect, analyze and troubleshoot their runs in the Azure ML workspace. With the new Cross-Experiment Run Comparison, Data Scientists can analyze their runs by graphically comparing and visualizing runs on the charts across some or all their experiments in a workspace. Users can also monitor their run progress, status and compare run performance which are essential tasks for both administrators and data scientists performing machine learning tasks. The new Custom Views allow users to customize their run analysis views and more effectively organize and keep track of their runs. The simplicity of sharing Custom Views allows for enhanced collaboration across colleagues and data scientist teams. Get 75% off on your Virtual ODSC East 2021 pass - https://bit.ly/2JkNAmA ODSC Links: • Get free access to more talks/trainings like this at AI+ Training platform: https://aiplus.odsc.com/ • Facebook: https://www.facebook.com/OPENDATASCI • Twitter: https://twitter.com/odsc & @odsc • LinkedIn: https://www.linkedin.com/company/open-data-science • Slack Channel: http://bit.ly/2RkOf9l • APAC Conference 8th–9th December 2020: https://odsc.com/apac/ • East Conference March 30th - April 1st: https://odsc.com/boston/ • Code of conduct: https://odsc.com/code-of-conduct/

Photos (54)