We host Machine Learning and MLOps related bi-weekly webinars.
LayoutParser is a deep learning-based tool that helps identify documents’ visual layouts and extract structured information from them. However, end users commonly encounter unique layouts that require data annotation and fine-tuning a customized model in order to achieve an ideal accuracy. In this webinar, we will show how to build one such model for scientific PDF extraction as an example. We will use label-studio for creating the training dataset, and we will fine-tune and use the layout detection model in LayoutParser.
A long requested comprehensive overview of an important Label Studio feature, building custom frontends. More details to follow.
Join Heartex's Label Studio Product Designer Den Talata for a look ahead at an often requested exciting new feature: Video Annotation
An upcoming partner webinar featuring Activeloop - additional details to follow.
An interview with Unbiased AI CEO Sukesh Tedla about how to create a transparent, trustworthy data platform for AI with blockchain technology
Jina is an open source neural search framework that empowers anyone to build SOTA and scalable deep learning search applications in minutes.
Effective Active Learning Techniques ft. Lightly co-founder Igor Susmelj, ML Engineer Malte Ebner & Heartex CTO Nikolai Liubimov
A tutorial showing a demo integration with Amazon SageMaker hosted by Sarah Moir, head of Content & Education at Heartex.
Learn the advantages of using Bayesian active learning (BaaL) versus regular active learning featuring Servicenow Applied Research Scientists Frederic Branchaud-Charron & Parmida Atighehchian in conversation with Heartex CEO Michael Malyuk
Join Senior Frontend Engineer Nick Skriabin for an overview of whats new, fixed and great about Label Studio Open Source version 1.1
Featuring Machine Learning expert and active Label Studio community member Aaron Soellinger. Hosted by Heartex's Head of Open Source Community Michael Ludden.
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