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 (3)

Webinar: "Sharing Large Amounts of Data with Open Source Delta Sharing"

To access this webinar, please register here:
https://attendee.gotowebinar.com/register/1795336879817942285

Topic: Sharing Large Amounts of Data with Open Source Delta Sharing

Speaker: Dr. Frank Munz, Developer Advocate at Databricks
https://www.linkedin.com/in/frankmunz/

Bio:
Dr. Frank Munz authored three computer science books, built up technical evangelism for Amazon Web Services in Germany, Austria and Switzerland and once upon a time worked as data scientist with a group that won a Nobel prize for linking HPV to cancer.

Frank realized his dream to speak at top-notch conferences on every continent (except antarctica, because it is too cold there) such as re:Invent, Devoxx, Kubecon, and Java One. He holds a PhD in Computer Science from TU Munich.

Abstract:
In this session, speaker will dive deep into Delta Sharing; A Linux Foundation open source solution for sharing massive amounts of data in a cheap, secure, and scalable way.

Delta Sharing reliably accesses data at the bandwidth of modern cloud object stores, such as S3, ADLS, or GCS. The data provider runs a sharing server and decides what data to share. To get you started, a hosted reference sharing service, an open-sourced pre-packaged server, and a Docker image are available for sharing data from your lakehouse.

Under the hood, Delta Sharing uses an open REST protocol, enabling secure data sharing across products and companies for the first time.
Any client supporting pandas, Apache Spark™, or Python, can connect to the sharing server. Clients always read the latest version of the data, and they can provide filters on partitioned data to read a subset of the data.

This talk is built around a number of hands-on demos: We start with a multi-cloud example using Google Colab. Then speaker will share some raw data of the sampled DNA using Delta Sharing and we will build a client in pandas. The client will then check for genetic traits, such as eye color, the coffee metabolism rate, special nutritional requirements etc. All data access is read-only, there will be no harm to the presenter. To conclude, we will compare running your own self-hosted Delta Sharing server with sharing data from a managed cloud service using SQL.

[November] Get your Pass to ODSC West 2021 with an additional discount - https://bit.ly/3fGU0sS or Virtual pass - https://bit.ly/2SXM2E4

[18th November] Free Virtual Ai+ Professionals Expo - https://hubs.li/H0Y8St80

ODSC Links:
• Get free access to more talks/trainings like this at AI+ Training platform:
https://aiplus.training/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://bit.ly/35pfPZo
• ODSC West Kickstart Bootcamp Nov 15th - 18th - https://odsc.com/california/bootcamp/
• West Conference November 16th - 18th: https://odsc.com/california/
• Code of conduct: https://odsc.com/code-of-conduct/

Lessons From the Field in Building Your Enterprise MLOps Strategy

To access this webinar, please register here:
https://attendee.gotowebinar.com/register/6301849113648201995

Topic: Lessons From the Field in Building Your Enterprise MLOps Strategy

Speaker: Harpreet Sahota, Data Scientist, Comet

Harpreet is a thought leader in the Data Science space and hosts The Artists of Data Science podcast

Abstract: As machine learning expands across industries and larger organizations begin deploying across bigger teams, the need to efficiently operationalize becomes critical for enterprises. In our discussions with leading organizations utilizing ML, we have compiled real-world case studies and organizational best practices for MLOps in the enterprise.

Join us for a discussion where we'll explore the benefits of MLOps and discuss when and how to deploy MLOps in your machine learning efforts where we review three real world case studies that will answer key questions:

When to start investing in MLOps?
How to start investing in MLOps?
How to measure the success of your MLOps strategy

[18th November] Free Virtual Ai+ Professionals Expo - https://hubs.li/H0Y8St80

[November] Get your Pass to ODSC West 2021 with an additional discount - ttps://hubs.li/H0YWJD60 or Virtual pass - https://hubs.li/H0YWJvs0

ODSC Links:
• Get free access to more talks/trainings like this at AI+ Training platform:
https://aiplus.training/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://bit.ly/35pfPZo
• ODSC West Kickstart Bootcamp Nov 15th - 18th - https://hubs.li/H0YWLND0
• West Conference November 16th - 18th: https://hubs.li/H0YWM6w0
• Code of conduct: https://odsc.com/code-of-conduct/

LIVE TRAINING: October 28th: Gradient Boosting for Prediction and Inference

This is a PAID event.

Registration is required: https://aiplus.training/live/gradient-boosting-for-prediction-and-inference-live-training/

Level INTERMEDIATE

Instructor's bio: Brian Lucena,PhD, Principal | Numeristical

Brian Lucena is Principal at Numeristical and the creator of StructureBoost, ML-Insights, and SplineCalib. His mission is to enhance the understanding and application of modern machine learning and statistical techniques. He does this through academic research, open-source software development, and educational content such as live stream classes and interactive Jupyter notebooks. Additionally, he consults for organizations of all sizes from small startups to large public enterprises. In previous roles, he has served as SVP of Analytics at PCCI, Principal Data Scientist at Clover Health, and Chief Mathematician at Guardian Analytics. He has taught at numerous institutions including UC-Berkeley, Brown, USF, and the Metis Data Science Bootcamp.

Abstract:

Gradient Boosting is widely used in prediction problems across industry and academia. Common applications include fraud detection, home price prediction, and loan default prediction, just to name a few. This course is an intensive hands-on workshop with real data sets focused on using Gradient Boosting for classification and regression problems. Participants will gain valuable experience training, evaluating, and drawing conclusions from Gradient Boosting models. They will gain familiarity with Gradient Boosting packages such as XGBoost, LightGBM, CatBoost, and StructureBoost. By the end of the course, participants will feel confident that they understand the details and parameters behind Gradient Boosting, and be able to present, criticize, and defend the models they create.

Course Outline
1. Background: Decision Trees, and Random Forests
2. Gradient Boosting: Definition and History
3. Review of gradient Boosting Packages
4. Interpreting and Understanding Gradient Boosting Models
5. Application to Medical Data

Which knowledge and skills you should have?
This course is geared to data scientists of all levels who wish to gain a deep understanding of Gradient Boosting and how to apply it to real-world situations. The ideal participant will have some experience with building models. They should know the Python data science toolkit (numpy, pandas, scikit-learn, matplotlib) and have experience fitting models on training sets, making predictions on test sets, and evaluating the quality of the model with metrics.

What is included in your ticket?
1. Access to the live training and a QA session with the Instructor
2. Access to the on-demand recording
3. Certificate of completion

[November]Get your Pass to ODSC West 2021 with an additional discount - https://bit.ly/3fGU0sS or Virtual pass - https://bit.ly/2SXM2E4

[18th November]Free Virtual Ai+ Professionals Expo - https://hubs.li/H0Y8St80

ODSC Links:
• Get free access to more talks/trainings like this at AI+ Training platform:
https://aiplus.training/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://bit.ly/35pfPZo
• ODSC West Kickstart Bootcamp Nov 15th - 18th - https://odsc.com/california/bootcamp/
• West Conference November 16th - 18th: https://odsc.com/california/
• Code of conduct: https://odsc.com/code-of-conduct/

Past events (118)

Photos (182)