le_james94
Re:Marengo 3.0: A Production-Grade Video Foundation Model from TwelveLabs
on Monday December 01, 2025 @11:32AM (#46109395)
Marengo 3.0 represents a fundamental shift from benchmark optimization to production-grade video understanding. By natively supporting multilingual content, composed queries, hour-long videos, and specialized domains like sports—while maintaining leadership on general benchmarks—we have built a foundation model that scales with real-world complexity.
Marengo 3.0: A Production-Grade Video Foundation Model from TwelveLabs
Basics of Data Integration
Components Towards Building Production-Ready Machine Learning Systems
Variants of Matrix Factorization for Collaborative Filtering
Basics of Data Cleaning
Exploring Itemset Mining
Clustering Algorithms Explained
Basics of Decision Trees
Distributed Data Processing
Troubleshooting Deep Neural Networks
Operationalize Data Science Projects in the Real World
Open-Source Data Science for Business Leaders
Running an effective data science POC
Concepts in Data Management
Machine Learning Teams
Set Up Machine Learning Projects
Deep Learning Infrastructure at Scale
Research Directions for Recommendation Systems
Categories of deep recommendation systems
An Executive Guide to Building Recommendation System
A Friendly Introduction to Data-Driven Marketing Business Leaders
What I Learned from Attending All Tech Is Human NYC 2019
The 4 Steps To Build Out Your Machine Learning Team Productively
Steps to Set Your Machine Learning Projects Up for Success
Re:The 7 Questions You Need to Ask to Operate Deep Learning Infrastruc...
on Saturday December 14, 2019 @10:48PM (#21794328)
The portion of ML code in a real-world ML system is a lot smaller than the infrastructure needed for its support. In this blog post, I would like to share the 7 questions that you and your colleagues should ask to handle deep learning technical debt.