ODSC Silicon Valley Data Science

To access this webinar, please register here: https://hubs.li/Q01DptBx0

Topic: "Making Machine Learning Easy for Engineers with Declarative ML"

Speaker#1: Devvret Rish, Co-Founder and Chief Product Officer, Predibase
Prior to Predibase, he was a ML PM at Google working across products like Firebase, Google Research and the Google Assistant as well as Vertex AI. While there, Dev was also the first product manager for Kaggle – a data science and machine learning community with over 8 million users worldwide. Dev’s academic background is in computer science and statistics, and he holds a masters in computer science from Harvard University focused on machine learning.

Speaker#2: Geoffrey Angus, Machine Learning Engineer at Predibase
Prior to Predibase, he worked at Google Research on the Perception team. While there, he implemented, trained, and deployed large multi-modal models for Image Search and Google Lens. Geoffrey holds a Bachelor's and Master's in Computer Science from Stanford University, where he conducted machine learning research on weak supervision and computer vision for medical imaging applications.

Abstract:
Making ML easy and accessible for engineers through low-code interfaces.

At some point, every engineering team’s roadmap has included an item to “improve their product with machine learning”. Depending on the product, this can mean anything from adding personalization, recommender systems, fraud detection, or any ML-powered feature that leverages collected data to improve the user experience.
The challenge: most organizations lack sufficient data science resources to rapidly build custom models in-house, leaving engineering teams roadblocked on their ML projects and the OKR is pushed back another quarter.

A new generation of declarative machine learning tools—built on foundations pioneered at Uber, Apple, and Meta—aims to change this dynamic by making machine learning accessible to engineers and teams that are ML-curious. Declarative ML systems simplify model building with a config-driven approach rooted in engineering best practices like automation and reusability, in a similar way that Kubernetes revolutionized managing infrastructure. With these capabilities, developers can build powerful production-grade ML systems for practical applications in minutes.

Join this webinar and demo to learn:
- About declarative ML systems, incl. open-source Ludwig from Uber
- How to build state-of-the-art machine learning and deep learning models in less than 15 lines of code
- How to rapidly train, iterate, and deploy a multimodal deep learning model with Ludwig and Predibase

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/Q01C4bDY0
• ODSC East 2023 May 9-11th - https://hubs.li/Q01nwjvl0
• ODSC Europe 2023 June 14th-15th - https://hubs.li/Q01t57Dd0
• Code of conduct: https://odsc.com/code-of-conduct/

This is PAID event.
More info you may find here - https://hubs.li/Q01nwjvl0
Use COMMUNITY2023 code for an extra discount.
Virtual tickets - https://hubs.li/Q01xMs7_0
In-person tickets - https://hubs.li/Q01xMsd60

Speakers like Pedro Domingos, PhD, Raluca Ada Popa, PhD, Dr. Jon Krohn, Tamilla Triantoro, PhD, Ariel Procaccia, PhD, Dan Roth, PhD, Stefanie Molin, Aric LaBarr, PhD, Dr. Hongxia Yang, PhD and more - are waiting for you!

Preliminary schedule is available here - https://hubs.li/Q01BQCWL0
Confirmed session titles include

• NLP Fundamentals
• Deep Learning with PyTorch and TensorFlow
• Synthetic Data in Healthcare: Methods, Challenges, and Use Cases
• Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI
• Modern NLP: Pre-training, Fine-tuning, Prompt Engineering, and Human Feedback
• Introduction to AutoML: Hyperparameter Optimization and Neural Architecture Search
• Hyper-productive NLP with Hugging Face Transformers
• Beyond the Basics: Data Visualization in Python
• Introduction to Large-scale Analytics with PySpark
• A Practical Tutorial on Building Machine Learning Demos with Gradio
• Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI

We’ll be adding more titles soon, so be sure to check back often.

At ODSC East you’ll find an unprecedented breadth and depth of data science topics, tools, languages, frameworks, and platforms, making it the can’t-miss conference for data scientists and AI professionals of all levels, beginner to advanced.

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/Q01C4bDY0
• ODSC East 2023 May 9-11th - https://hubs.li/Q01nwjvl0
• ODSC Europe 2023 June 14th-15th - https://hubs.li/Q01t57Dd0
• Code of conduct: https://odsc.com/code-of-conduct/