AI Blog

MLOps NYC Panel: Recorded Sessions

October 17, 2019

It's a wrap! We had a full house at MLOps NYC, Iguazio's annual conference about managing and automating machine learning pipelines in order to bring data science into business applications. With an outstanding caliber of speakers and audience, the MLOps conference went beyond theory, shedding light on painful and successful machine learning experiences which involve...

ML

Modernize your IT Infrastructure Monitoring by Combining Time Series Databases with Machine Learning

August 12, 2019

Let’s explore the complexity and vulnerability of IT infrastructure and how to build a modern IT infrastructure monitoring solution, using a combination of time series databases with machine learning.

ML

Python Pandas at Extreme Performance

August 8, 2019

Today we all choose between the simplicity of Python tools (pandas, Scikit-learn), the scalability of Spark and Hadoop, and the operation readiness of Kubernetes. We end up using them all.

ML

Why is it So Hard to Integrate Machine Learning into Real Business Applications?

July 20, 2019

You’ve played around with machine learning, learned about the mysteries of neural networks, almost won a Kaggle competition and now you feel ready to bring all this to real world impact. It’s time to build some real AI-based applications.

Azure Intelligent Edge MLOps

Automating Machine Learning Pipelines on Azure and Azure Stack

July 15, 2019

Ever wonder if it’s possible to train machine learning (ML) models with regulated data which can’t be sent to the cloud? Has your edge solution gathered so much data that it just doesn’t make sense to send it all to
the cloud?

Data science GPUs Horovod NVIDIA

Horovod for Deep Learning on a GPU Cluster

July 1, 2019

Here’s the problem: we are always under pressure to reduce the time it takes to develop a new model, while datasets only grow in size. Running a training job on a single node is pretty easy, but nobody wants to wait hours and then run it again, only to realize that it wasn’t right to begin with.

2025 Gen AI Predictions: What Lies Ahead?

MLOps NYC Panel: Recorded Sessions

Modernize your IT Infrastructure Monitoring by Combining Time Series Databases with Machine Learning

Python Pandas at Extreme Performance

Why is it So Hard to Integrate Machine Learning into Real Business Applications?

Automating Machine Learning Pipelines on Azure and Azure Stack

Horovod for Deep Learning on a GPU Cluster

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