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Machine Learning

N-shot and Zero-shot learning with Python

By Dr Behzad Javaheri

Perspective

Want to Make Your Data Scientists Un-poachable? Consider These Top Expert Tips

By Lisa Stapleton

Perspective

Serious About AI? You Need a GPU Strategy

By Kjell Carlsson

Perspective

How Enterprise MLOps Turbocharges Data Science: 4 Real-World Use Cases

By Josh Poduska

Code

Getting Started with OpenCV

By Dr Behzad Javaheri

Product Updates

Domino 5.0: Securely store credentials to support compliance requirements

By Elliott Whiting

Machine Learning

Speeding up Machine Learning with parallel C/C++ code execution via Spark

By Nikolay Manchev

Product Updates

Domino 5.0: Up-Level Your 'Laptop-in-the-Cloud' Experience for the Best of Both Worlds

By Deepam Dubey

Product Updates

Domino 5.0: Easily leverage Git repositories to increase model velocity

By May Hu

Product Updates

Domino 5.0: Develop Better Models Faster With Auto-Scaled Distributed Compute

By Alireza Mounesisohi and Lakshmi Narayanan

Product Updates

Domino 5.0: share and reuse trusted data sources to drive model quality

By Andrew Coleman

Product Updates

Domino 5.0: Accelerate the Root Cause Analysis of Model Drift

By Vinay Sridhar

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Product Updates

Domino 5.0: Rapidly Update Production Models for Optimal Performance

Machine Learning

Semi-uniform strategies for solving K-armed bandits

By Nikolay Manchev

Product Updates

Domino 5.0: Unleashing Model Velocity

By Bob Laurent

Perspective

Model velocity: the key to accelerating your model-driven business

By Kjell Carlsson

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Domino Data Lab empowers the largest AI-driven enterprises to build and operate AI at scale. Domino’s Enterprise AI Platform provides an integrated experience encompassing model development, MLOps, collaboration, and governance. With Domino, global enterprises can develop better medicines, grow more productive crops, develop more competitive products, and more. Founded in 2013, Domino is backed by Sequoia Capital, Coatue Management, NVIDIA, Snowflake, and other leading investors.

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