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🎉 We released Spotlight 1.6.0 check it out

8 posts tagged with "data-centric ai"

· 8 min read
Voice analytics helps to build more sympathetic and more robust ML-based assistants. We show how to leverage open source tooling to effectively use pre-trained transformer models for this use case.
voice analyticsaudio mldata-centric ai

· 14 min read
Data slices are semantically meaningful subsets of the data, where the model performs anomalously. We discuss current challenges and demonstrate hands-on examples of opens source tooling.
data-centric aidata slicingcomputer vision

· 12 min read
Fine-tuning significantly influences embeddings in image classification. Pre-fine-tuning embeddings offer general-purpose representations, whereas post-fine-tuning embeddings capture task-specific features. This distinction can lead to varying outcomes in outlier detection and other tasks. Both pre-fine-tuning and post-fine-tuning embeddings have their unique strengths and should be used in combination to achieve a comprehensive analysis in image classification and analysis tasks.
computer visiondata-visualizationdata-centric ai

· 10 min read
The Industrial AI Canvas can be a useful tool for planning data and ml-based projects.
Data-centric AIdata curationproject managementuse case assessment

· 4 min read
If you work in ML-based acoustics, the annual DCASE challenge is a great resource to learn about new state-of-the-art methods. We built an enriched dataset for the condition monitoring task that can be downloaded from Huggingface and explored with Spotlight in just five minutes.
data-centric AIdata curationanomaly detectionacoustics

· 7 min read
We have just released the open version of our data curation software Renumics Spotlight. It is intended for cross-functional teams who want to be in control of their data and data curation processes. In this post I would like to share our ideas behind this product.
data-centric AIdata curation

· 6 min read
Selecting samples for training robust surrogate models in simulation can be a real challenge. Active learning-like approaches where samples are selected iteratively can help overcome this challenge. We show how to apply such a procedure to save time and computational resources while making your surrogate model even more robust.
visual inspectiondata curationLookout for Visionproductiondata-centric AIMLOpscloud

· 10 min read
Building robust models for Visual Inspection in production settings can be a real challenge. Here, cloud services like Amazon Lookout for Vision promise relief for model training but have limitations regarding data curation. This article explores those potential shortcomings and shows how to improve over them to leverage these services to the fullest.
visual inspectiondata curationLookout for Visionproductiondata-centric AIMLOpscloud