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Managing Computer Vision Projects with Micha? Tadeusiak 

The MLOps Blog

Every episode is focused on one specific ML topic, and during this one, we talked to Michal Tadeusiak about managing computer vision projects. I’m joined by my co-host, Stephen, and with us today, we have Michal Tadeusiak , who will be answering questions about managing computer vision projects.

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Streamline diarization using AI as an assistive technology: ZOO Digital’s story

AWS Machine Learning Blog

This time-consuming process must be completed before content can be dubbed into another language. Through automation, ZOO Digital aims to achieve localization in under 30 minutes. However, the supply of skilled people is being outstripped by the increasing demand for content, requiring automation to assist with localization workflows.

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Journey using CVAT semi-automatic annotation with a partially trained model to tag additional…

Mlearning.ai

that comply to YOLOv5 with specific requirement on model output, which easily got mess up thru conversion of model from PyTorch > ONNX > Tensorflow > TensorflowJS) Computer Vision Annotation Tool (CVAT) CVAT is build by Intel for doing computer vision annotation which put together openCV, OpenVino (to speed up CPU inference).

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MLOps Landscape in 2023: Top Tools and Platforms

The MLOps Blog

This includes features for hyperparameter tuning, automated model selection, and visualization of model metrics. Automated pipelining and workflow orchestration: Platforms should provide tools for automated pipelining and workflow orchestration, enabling you to define and manage complex ML pipelines.

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How Forethought saves over 66% in costs for generative AI models using Amazon SageMaker

AWS Machine Learning Blog

The integration of large language models helps humanize the interaction with automated agents, creating a more engaging and satisfying support experience. In addition, deployments are now as simple as calling Boto3 SageMaker APIs and attaching the proper auto scaling policies. The following diagram illustrates our legacy architecture.

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How United Airlines built a cost-efficient Optical Character Recognition active learning pipeline

AWS Machine Learning Blog

In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab , build an active learning framework on AWS to automate the processing of passenger documents. “In We used Amazon Textract to automate information extraction from specific document fields such as name and passport number.

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Training large language models on Amazon SageMaker: Best practices

AWS Machine Learning Blog

Although this post focuses on LLMs, most of its best practices are relevant for any kind of large-model training, including computer vision and multi-modal models, such as Stable Diffusion. Amazon FSx is an open-source parallel file system, popular in high-performance computing (HPC). Note that effective in NCCL 2.12