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:

• Meetup/Webinar Speaker Submission Form https://forms.gle/STEDWxgWBMnLnt8F8

• Suggest a Meetup Topic Form
https://forms.gle/FAnBGMnC6puP1zLs6

• Volunteer Form
https://forms.gle/rJB2k8ZvU7mj1R3c8

• Host or Sponsor Form
https://forms.gle/bVdnzttfSuKkWrHq5

• Showcase your Startup Form
https://forms.gle/2Z31dmGPe7RTw28B9

ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q018SM1r0
• ODSC Europe 2022 June 15th-16th - https://hubs.li/Q012hpDP0
• ODSC APAC 2022 September 7th-8th - https://hubs.li/Q01bgr6W0
• Code of conduct: https://odsc.com/code-of-conduct/

Upcoming events (2)

Webinar "Form Recognizer 3.0: Document Understanding"

Link visible for attendees

To access this webinar, please register here: https://hubs.li/Q01sqRkn0

Topic: "Form Recognizer 3.0: Document Understanding"

Speaker: Bema Bonsu, Product Manager at Microsoft

Bema is part of Form Recognizer team. They are working to bring you cloud based solutions to your document processing and understanding needs!

Abstract:
Form Recognizer 3.0 is now Generally available!
Join this session to learn more about the new features and services available through Form Recognizer to make document processing and automation even easier and more streamlined.

ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q01rNXcm0
• ODSC East 2023 May 9-11th - https://hubs.li/Q01nwjvl0
• Code of conduct: https://odsc.com/code-of-conduct/

Webinar "Using Open Source for Failure Prediction"

Link visible for attendees

To access this webinar, please register here: https://hubs.li/Q01sqR-60

Topic: "Using Open Source for Failure Prediction"

Speaker: Audrey Reznik, Sr. Principal Software Engineer at Red Hat

Audrey is part of Red Hat OpenShift Data Science team focusing on helping customers with managed services, AI/ML workloads and next-generation platforms. She holds degrees in Computer Information Systems and Geology, and has work experience in each field. Audrey is passionate about Data Science and in particular the current opportunities with AIML at the Edge and Open Source technologies.

Abstract:
Failure prediction in real time on time series data can be realized with the use of Open Source tools. We will deliver an overall view of how to start with the generation of new raw sensor data (typically captured by an Edge device), and end up with a real time graph that shows alerts warning that a failure is imminent. There are a number of processes that must be put into place before the stated goal can be fully realized.

In particular, we will first need a data collector whose job is to receive the raw sensor data and then put that data into a data storage unit. All of the new raw sensor data are associated with the timestamp of when the sensor data point was generated, thereby forming what is called a time series. The data collector then, by socket communication sends the new data to a web application that puts the new data into a form that enables a trained Machine Learning model to make a binary classification (Normal or Not Normal) prediction. A real time time series graph is then updated with the prediction, and the data is pushed to a browser where the real time graph is rendered. All of the processes mentioned above can be implemented with the use of Open Source tooling.

ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q01rNXcm0
• ODSC East 2023 May 9-11th - https://hubs.li/Q01nwjvl0
• Code of conduct: https://odsc.com/code-of-conduct/

Past events (52)

Webinar "CI/CD for Machine Learning"

This event has passed

Photos (301)