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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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The Marvels of Generative AI: Key Concepts and Use Cases

Data Science Dojo

In the media, it can produce entirely new musical compositions or write compelling articles. How Generative AI Works Generative AI operates by learning from vast amounts of data to generate new content that mimics the original data in form and quality. Supervised Learning: The AI learns from a dataset that has predefined labels.

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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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AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the difference?

IBM Journey to AI blog

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Retell a Paper: “Self-supervised Learning in Remote Sensing: A Review”

Mlearning.ai

NOTES, DEEP LEARNING, REMOTE SENSING, ADVANCED METHODS, SELF-SUPERVISED LEARNING A note of the paper I have read Photo by Kelly Sikkema on Unsplash Hi everyone, In today’s story, I would share notes I took from 32 pages of Wang et al., 2022 Deep learning notoriously needs a lot of data in training.

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Reinforcement Learning: Markov Decision Process — Part 1

Towards AI

Introducing the backbone of Reinforcement Learning — The Markov Decision Process This member-only story is on us. Image by Ricardo Gomez Angel on Unsplash In most of my previous articles, I have mostly discussed Supervised Learning, with some sprinkling of elements of Unsupervised Learning.