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)

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/

Photos (116)