2024年2月23日 · Developed with extensive input from experts here at SiMa.ai and across the industry, we call this new lifecycle CRISP-EML, or Cross-Industry Standard Process for Embedded Machine Learning. CRISP-EML hopes to encapsulate a fresh perspective on the nuances, personas, and requirements for the unique challenge of developing ML-driven embedded systems.

To guide ML practitioners through the development life cycle, the Cross-Industry Standard Process for the development of Machine Learning applications with Quality assurance methodology (CRISP-ML (Q)) was recently proposed. We review the core phases of the ML development process model (see Figure 1).

On Edge is back! In our latest episode, hosts Carlos and Alicja present a new methodology and lifecycle diagram for embedded AI development. Building on exis...

To leverage these advancements while keeping the system compliant for safety critical applications, this paper reviews the challenges of using open source ML models for safety critical applications and proposes metrics and workflow to improve model …

2024年11月25日 · The CRISP-ML (Q) framework, an adaptation of the well-known CRISP-DM (Cross-Industry Standard Process for Data Mining), is a structured approach for executing machine learning (ML) projects. It...

Carlos Davila introduces a new framework called Cross-Industry Standard Process for Embedded Machine Learning or CRISP-EML as a new methodology for embedded ML development. He also guides readers ...

2023年12月19日 · Using SiMa.ai CEO Krishna Rangasayee’s recent blog post as a blueprint for their discussion, our hosts give us their own detailed take on three key predictions for the coming year: Domain specialized models. Scaling back on parameter width is critical given current capacity limitations.

2025年2月12日 · To address these challenges, we present a pipeline that automatically generates high-quality segmentation maps from cryo-EM data to serve as ground truth labels. Our modular framework enables the selection of various segmentation models and loss functions.

2021年10月25日 · Parses forwarded emails and extracts original content. This library supports most common email clients and locales. 😘 Maintainer: @eliottvincent. Who uses it? 👋 You use this library and you want to be listed there? Contact us. This library is used at Crisp everyday with around 1 million inbound emails.

🙌 Welcome to a new episode of OnEdge, our YouTube series that examines the most important topics to ML Developers. In this installment, Carlos Davila and…