Search Results for: machine learning

Wallaroo Introduces Free Community Edition to Democratize Production Machine Learning

Wallaroo Labs announced the general availability launch of its new, free Community Edition (Wallaroo CE) version of its enterprise product that helps teams speed up and simplify the deployment and operations of machine learning (ML) models and pipelines in production. For too long, the perception was that scaling ML required unlimited resources or specific skills/expertise for data scientists and ML engineers.

Reforming Prior Authorization with AI and Machine Learning

In this contributed article, Niall O’Connor, CTO at Cohere Health, discusses how the application of AI and ML to the onerous prior authorization (PA) process can relieve both physicians and health plans of the repetitive, manual administrative work involved in submitting and reviewing these requests. Most importantly, these intelligent technologies transform PA from a largely bureaucratic exercise into a process that is capable of ensuring that patients receive the highest quality of care, as quickly and painlessly as possible.

Predibase Introduces a New Way to Do Low-Code Machine Learning

Predibase emerged from stealth with its commercial platform that lets both data scientists and non-experts develop flexible, state-of-the-art ML with best-of-breed ML infrastructure. Predibase has been in beta with Fortune 500 enterprises the last nine months who have seen time for model development deployment drop from months to days and used by data practitioners and engineers across each organization. 

Galileo Launches to Give Data Scientists the Superpowers They Need for Unstructured Data Machine Learning

Galileo emerged from stealth with the first machine learning (ML) data intelligence platform for unstructured data that gives data scientists the ability to inspect, discover and fix critical ML data errors 10x faster across the entire ML lifecycle – from pre-training to post-training to post-production. The platform is currently in private beta with the Fortune 500 and startups across multiple industries.

Baseten Gives Data Science and Machine Learning Teams the Superpowers They Need to Build Production-Grade Machine Learning-Powered Apps

Baseten formally launched with its product that makes going from machine learning model to production-grade applications fast and easy by giving data science and machine learning teams the ability to incorporate machine learning into business processes without backend, frontend or MLOps knowledge. The product has been in private beta since last summer with well-known brands that have used it for everything from abuse detection to fraud prevention. It is in public beta at this time.

Comet Reveals Machine Learning Survey Results

Comet, the provider of the leading development platform for enterprise machine learning (ML) teams, announced the results of its recent survey of machine learning professionals. Hundreds of enterprise ML team leaders were asked about their experiences and the factors that affected their teams’ ability to deliver the level of business value their organizations expected from ML initiatives.

Book Review: Machine Learning with PyTorch and Scikit-Learn

The enticing new title courtesy of Packt Publishing, “Machine Learning with PyTorch and Scikit-Learn,” by Sebastian Raschka, Yuxi (Hayden) Liu, and Vahid Mirjalili is a welcome addition to any data scientist’s list of learning resources. This 2022 tome consists of 741 well-crafted pages designed to provide a comprehensive framework for working in the realm of machine learning and deep learning. The book is brimming with topics that will propel you to a leading-edge understanding of the field.

SPEC Establishes Machine Learning Committee to Develop Vendor-Agnostic Benchmarks

The Standard Performance Evaluation Corp. (SPEC) announced the formation of the SPEC Machine Learning Committee. The SPEC ML Committee will develop practical methodologies for benchmarking artificial intelligence (AI) and machine learning (ML) performance in the context of real-world platforms and environments.

University of Illinois Professor’s Expertise in Machine Learning for Audio Benefits Creation of New Beatles Documentary

From the first time he used a synthesizer, Illinois Computer Science professor Paris Smaragdis knew that he wanted to learn how technology could make or alter music. What’s followed is a career in academia that centered his Artificial Intelligence research on the question: What does it mean to take a stream of sound and then break it down into its individual components? Nothing he’s accomplished has been more “mind-bending” than the recent work he completed with a team of engineers to boost the audio quality of director Peter Jackson’s recent documentary titled “The Beatles: Get Back.”

apply() meetup | February 10, 2022 – A free virtual event on data engineering for applied Machine Learning

Join Tecton at #applyCommunityMeetup, February 10, presented by tectonAI and other apply() partners. Learn the latest trends and new best practices for #MLOps and ML data engineering! Grab your FREE ticket today!