Remove Categorization Remove Natural Language Processing Remove Neural Network
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This AI Paper from King’s College London Introduces a Theoretical Analysis of Neural Network Architectures Through Topos Theory

Marktechpost

King’s College London researchers have highlighted the importance of developing a theoretical understanding of why transformer architectures, such as those used in models like ChatGPT, have succeeded in natural language processing tasks.

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This AI Paper from UCLA Revolutionizes Uncertainty Quantification in Deep Neural Networks Using Cycle Consistency

Marktechpost

With the growth of Deep learning, it is used in many fields, including data mining and natural language processing. However, deep neural networks are inaccurate and can produce unreliable outcomes. It can improve deep neural networks’ reliability in inverse imaging issues.

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Understanding Graph Neural Network with hands-on example| Part-1

Becoming Human

This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications. Through the next series of this post here , I will try to make an implementation of Graph Convolutional Neural Network. How do Graph Neural Networks work?

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Making Sense of the Mess: LLMs Role in Unstructured Data Extraction

Unite.AI

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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Five machine learning types to know

IBM Journey to AI blog

Many retailers’ e-commerce platforms—including those of IBM, Amazon, Google, Meta and Netflix—rely on artificial neural networks (ANNs) to deliver personalized recommendations. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g.,

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10 Best AI Tools to Protect Your Brand and Streamline Influencer Marketing (December 2024)

Unite.AI

These innovative platforms combine advanced AI and natural language processing (NLP) with practical features to help brands succeed in digital marketing, offering everything from real-time safety monitoring to sophisticated creator verification systems.

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Huawei Researchers Introduce a Novel and Adaptively Adjustable Loss Function for Weak-to-Strong Supervision

Marktechpost

In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet. This approach has demonstrated effectiveness in natural language processing and reinforcement learning.