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DataRobot is Acquiring Algorithmia, Enhancing Leading MLOps Infrastructure to Get Models to Production Fast, with Optimized GPU Workloads at Scale

DataRobot

In a global marketplace where decision-making needs to happen with increasing velocity, data science teams often need not only to speed up their modeling deployment but also do it at scale across their entire enterprise. This allows for the pipelining of incredibly complex inference models.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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SAP Industry Insights Podcast Highlights of 2021 with Host Tom Raftery

Timo Elliott

I recently had the opportunity to sit down with Tom Raftery , host of the SAP Industry Insights Podcast (among others!) Most people rent skis rather than buying, because it’s easier and cheaper and more convenient — so why not apply that model to more things? The logic of the argument was very convincing.

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The DataOps Vendor Landscape, 2021

DataKitchen

We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Dagster / ElementL — A data orchestrator for machine learning, analytics, and ETL. . Meta-Orchestration .

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Big Data Has Transformed The Web Hosting Market On Both Ends

Smart Data Collective

Cloud technology has had a profound impact on the web hosting profession. Since big data has revolutionized the web hosting industry, a myriad of new hosting options are available. Big data is streamling hosting services, enhancing the user experience and improving customer support. Be Aware of Pricing Tricks.

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Building and Evaluating GenAI Knowledge Management Systems using Ollama, Trulens and Cloudera

Cloudera

Customizing Large Language Models (LLMs) is a great way for businesses to implement “AI”; they are invaluable to both businesses and their employees to help contextualize organizational knowledge. However, training models require huge hardware resources, significant budgets and specialist teams. Langchain) and LLM evaluations (e.g.

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5 ways to deploy your own large language model

CIO Business Intelligence

A large language model (LLM) is a type of gen AI that focuses on text and code instead of images or audio, although some have begun to integrate different modalities. But there’s a problem with it — you can never be sure if the information you upload won’t be used to train the next generation of the model. It’s not trivial,” she says.

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