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Top TensorFlow Courses

Marktechpost

By mastering TensorFlow, you gain valuable skills that can enhance your career prospects in the rapidly growing field of AI and machine learning. This article lists the top TensorFlow courses that can help you gain the expertise needed to excel in the field of AI and machine learning.

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Training a Custom Image Classification Network for OAK-D

PyImageSearch

Table of Contents Training a Custom Image Classification Network for OAK-D Configuring Your Development Environment Having Problems Configuring Your Development Environment? Furthermore, this tutorial aims to develop an image classification model that can learn to classify one of the 15 vegetables (e.g.,

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Building and Deploying CV Models: Lessons Learned From Computer Vision Engineer

The MLOps Blog

With over 3 years of experience in designing, building, and deploying computer vision (CV) models , I’ve realized people don’t focus enough on crucial aspects of building and deploying such complex systems. Hopefully, at the end of this blog, you will know a bit more about finding your way around computer vision projects.

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TinyML: Applications, Limitations, and It’s Use in IoT & Edge Devices

Unite.AI

In the past few years, Artificial Intelligence (AI) and Machine Learning (ML) have witnessed a meteoric rise in popularity and applications, not only in the industry but also in academia. To design it, the developers used the gestures data set, and used the data set to train the ProtoNN model with a classification algorithm.

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Benchmarking Computer Vision Models using PyTorch & Comet

Heartbeat

[link] Transfer learning using pre-trained computer vision models has become essential in modern computer vision applications. In this article, we will explore the process of fine-tuning computer vision models using PyTorch and monitoring the results using Comet. What comes out is amazing AI-generated art!

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This AI Paper Unveils X-Raydar: A Groundbreaking Open-Source Deep Neural Networks for Chest X-Ray Abnormality Detection

Marktechpost

Researchers from various universities in the UK have developed an open-source artificial intelligence (AI) system, X-Raydar, for comprehensive chest x-ray abnormality detection. The X-Raydar achieved a mean AUC of 0.919 on the auto-labeled set, 0.864 on the consensus set, and 0.842 on the MIMIC-CXR test. Check out the Paper.

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Build an image-to-text generative AI application using multimodality models on Amazon SageMaker

AWS Machine Learning Blog

Background of multimodality models Machine learning (ML) models have achieved significant advancements in fields like natural language processing (NLP) and computer vision, where models can exhibit human-like performance in analyzing and generating content from a single source of data.