ARTICLES
Why Governance Should Drive Your 2021 ML Strategy
Governance is one of the number one challenge organizations face with ML model deployment as they head into 2021.
Maximizing ML Infrastructure Tools for Production Workloads – Arize AI
Businesses in almost every industry are rapidly adopting Machine Learning (ML) technology and understanding the various platforms and offerings can be a challenge. The ML Infrastructure space is crowded, confusing, and complex.
Powering Up Your ML Monitoring in Production Now
Today's enterprises rely on machine learning-powered predictions to guide business strategy, such as by forecasting demand and mitigating risk. For an increasing number of businesses, machine learning (ML) underpin their core business model, like financial...
AI Alliance Member Tecton Secures $35M in Series B Funding and Delivers Their Feature Store to the World
Today marks a big milestone for Tecton. We’re excited to announce that the Tecton feature store is now in General Availability, and that we have raised $35 Million in Series B funding from our existing lead investors, Andreessen Horowitz and Sequoia, to fuel our next...
What is Data Lineage?
What is data lineage? At its most basic it’s the history of your data. It tells us where that data comes from, where it lives and how it’s transformed over time. As AI teams pour over data looking for patterns, or process it and massage it to get it into shape for...
Accelerate your Hyperparameter Optimization with PyTorch’s Ecosystem Tools
The design and training of neural networks are still challenging and unpredictable procedures. The difficulty of tuning these models makes training and reproducing more of an art than a science, based on the researcher’s knowledge and experience. One of the reasons...
Explainable Monitoring: Stop Flying Blind and Monitor Your AI – Fiddler Team
We’re living in unprecedented times wherein a matter of a few weeks, things changed dramatically for many humans and businesses across the globe. With COVID-19 spreading its wings across the globe and taking human lives we are seeing record jumps in unemployment and...
7 Rules for Bulletproof, Reproducible Machine Learning R&D
So, if you’re a nose-to-the-keyboard developer, there’s ample probability that this analogy is outside your comfort zone … bear with me. Imagine two Olympics-level figure skaters working together on the ice, day in and day out, to develop and perfect a medal-winning...
How to Improve Data Labeling Efficiency with Auto-Labeling, Uncertainty Estimates, and Active Learning
In this post we'll dive into the machine learning theory and techniques that were developed to evaluate our auto-labeling AI at Superb AI. More specifically, how our data platform estimates the uncertainty of auto-labeled annotations and applies it to active learning....
How the Canonical Stack for Machine Learning will Unleash the Next Generation of Cutting Edge AI Apps
The rise of the canonical stack in machine learning will change the way every company builds and develops AI/ML apps in the future, making it easier and faster to get started with advanced data science. Now companies will no longer need to build their own infrastructure from scratch. They can get right to building cutting edge models fast.
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