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Introduction to Supervised Deep Learning Algorithms!

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction This article aims to explain deep learning and some supervised. The post Introduction to Supervised Deep Learning Algorithms! appeared first on Analytics Vidhya.

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Brain MRI Segmentation with 0.95 Dice score

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Where our task will be to take brain MR images as input and utilize them with deep learning for automatic brain segmentation matured to a level […]. Introduction In this blog, we will try to solve a famously discussed task of Brain MRI segmentation.

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Data Science Journey Walkthrough – From Beginner to Expert

Smart Data Collective

What is data science? Data science is analyzing and predicting data, It is an emerging field. Some of the applications of data science are driverless cars, gaming AI, movie recommendations, and shopping recommendations. These data models predict outcomes of new data. Where to start?

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How to tackle lack of data: an overview on transfer learning

Data Science Blog

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

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Generative vs Discriminative AI: Understanding the 5 Key Differences

Data Science Dojo

A visual representation of discriminative AI – Source: Analytics Vidhya Discriminative modeling, often linked with supervised learning, works on categorizing existing data. This capability makes it well-suited for scenarios where labeled data is scarce or unavailable.

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Semi- and Self-Supervised Learning Help Clinicians Minimize Manual Labeling in Medical Image…

NYU Center for Data Science

Our study demonstrates that machine supervision significantly improves two crucial medical imaging tasks: classification and segmentation,” said Cirrone, who leads AI efforts at the Colton Center for Autoimmunity at NYU Langone.

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How Should Self-Supervised Learning Models Represent Their Data?

NYU Center for Data Science

Self-supervised learning (SSL) has emerged as a powerful technique for training deep neural networks without extensive labeled data. Rudner, among others, and “ To Compress or Not to Compress — Self-Supervised Learning and Information Theory: A Review.”