Search Results for: machine learning

Deploying Machine Learning Models at Scale: Strategies for Efficient Production

In this contributed article, freelance writer Ainsley Lawrence briefly explores deploying machine learning models, showing you how to manage multiple models, establish robust monitoring protocols, and efficiently prepare to scale. 

The Data Disconnect: A Key Challenge for Machine Learning Deployment

This article is excerpted from the book, “The AI Playbook: Mastering the Rare Art of Machine Learning Deployment,” by Eric Siegel, Ph.D., with permission from the publisher, MIT Press. It is a product of the author’s work while he held a one-year position as the Bodily Bicentennial Professor in Analytics at the UVA Darden School of Business. 

Book Review: A Hands-on Introduction to Machine Learning

I was pleased to receive a review copy of this new title from Cambridge University Press, “A Hands-on Introduction to Machine Learning.” The hardcover book is very attractive, well-produced and solid! It will weigh down your backpack for sure. As a university instructor myself, I immediately appreciated author and University of Washington professor Chirag Shah’s pedagogical approach.

2023 ML Pulse Report: The Latest Trends and Challenges in Machine Learning

Our friends over at Sama recently published a comprehensive report on the potential and challenges of AI as reported by Machine Learning professionals.

Video Highlights: Designing Machine Learning Systems — with Chip Huyen

Chip Huyen, co-founder of Claypot AI and author of O’Reilly’s best-selling “Designing Machine Learning Systems” joins our good friend Jon Krohn, Co-Founder and Chief Data Scientist at the machine learning company Nebula, to share her expertise on designing production-ready machine learning applications, the importance of iteration in real-world deployment, and the critical role of real-time machine learning in various applications.

DDN Storage Solutions Deliver 700% Gains in AI and Machine Learning for Image Segmentation and Natural Language Processing

DDN®, a leader in artificial intelligence (AI) and multi-cloud data management solutions, announced impressive performance results of its AI storage platform for the inaugural AI storage benchmarks released this week by MLCommons Association. The MLPerfTM Storage v0.5 benchmark results confirm DDN storage solutions as the gold standard for AI and machine learning applications.

NetSPI Debuts ML/AI Penetration Testing, a Holistic Approach to Securing Machine Learning Models and LLM Implementations

NetSPI, the global leader in offensive security, today debuted its ML/AI Pentesting solution to bring a more holistic and proactive approach to safeguarding machine learning model implementations. The first-of-its-kind solution focuses on two core components: Identifying, analyzing, and remediating vulnerabilities on machine learning systems such as Large Language Models (LLMs) and providing grounded advice and real-world guidance to ensure security is considered from ideation to implementation.

What is Automated Machine Learning (AutoML): How it Works and Best Practices

In this contributed article, AI, and computer vision enthusiast Melanie Johnson believes that as AutoML continues to progress, it holds the promise of enhancing efficiency and accuracy in machine learning tasks. However, it is crucial to strike a balance between automation and human expertise, leveraging AutoML as a valuable tool while still relying on domain knowledge and the skillful guidance of ML professionals. With continued advancements and collaboration, AutoML has the potential to drive innovation and create new opportunities in the realm of artificial intelligence and data analysis.

DDN is a Leading Data Storage Company Behind the Machine Learning and Generative AI Explosion

DDN®, a leader in artificial intelligence (AI) and multi-cloud data management solutions, announced that it has sold more AI storage appliances in the first four months of 2023 than it had for all of 2022. Broad enthusiasm for the business opportunities presented by generative AI has resulted in a steady increase in investment in AI and AI infrastructure.

How Machine Learning is Cleaning Up Medical Records

In this contributed article, Dr. Oleg Bess, practicing physician and CEO of 4medica, discusses how machine learning is doing great things in medicine, including improving medical diagnosis and drug manufacturing. It’s also improving healthcare in another way that doesn’t earn headlines but is at the core of care delivery: eliminating duplicate patient records, and providing high-quality data for patients and providers.