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This AI Research Shares a Comprehensive Overview of Large Language Models (LLMs) on Graphs

Marktechpost

Researchers have been studying how LLMs, with their good text-based reasoning, can be applied to basic graph reasoning tasks, including matching subgraphs, shortest paths, and connection inference. Six possible directions have been suggested for further research in the field of language models on graphs, delving into the fundamental ideas.

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This paper from Google DeepMind Provides an Overview of Synthetic Data Research, Discussing Its Applications, Challenges, and Future Directions

Marktechpost

By addressing the challenges and leveraging the potential of synthetic data responsibly and effectively, researchers can unlock new possibilities and drive the field of AI forward, ultimately benefiting society as a whole. All credit for this research goes to the researchers of this project. Check out the Paper.

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An Overview of Graph Machine Learning and Its Working

Analytics Vidhya

Active research is being done in this area (being touted by some as a new frontier of machine learning), and open-source libraries […]. The post An Overview of Graph Machine Learning and Its Working appeared first on Analytics Vidhya.

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Will MLOps change the future of the healthcare system?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Overview: From the advent of modern Science & Technology, Researchers are. The post Will MLOps change the future of the healthcare system? appeared first on Analytics Vidhya.

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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.

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MLOps Part 1: Revealing the Approach behind MLOps

Analytics Vidhya

Table of contents Overview Traditional Software development Life Cycle Waterfall Model Agile Model DevOps Challenges in ML models Understanding MLOps Data Engineering Machine Learning DevOps Endnotes Overview: MLOps According to research by deeplearning.ai, only 2% of the companies using Machine Learning, Deep learning have […].

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A Comprehensive Guide on Neural Networks Performance Optimization

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview Deep learning is a subset of Machine Learning dealing with different neural networks with three or more layers. There are different deep neural networks that work best on many different real-world applications and research and development are still going on.