Remove 10 machine-learning-models-comparative-analysis
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Google Research, 2022 & beyond: Algorithms for efficient deep learning

Google Research AI blog

The explosion in deep learning a decade ago was catapulted in part by the convergence of new algorithms and architectures, a marked increase in data, and access to greater compute. Beyond efficiency, there are a number of other challenges around factuality, security, privacy and freshness in these models.

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Explosion in 2022: Our Year in Review

Explosion

We’ve also released several updates to Prodigy and introduced new recipes to kickstart annotation with zero- or few-shot learning. During 2022, we also launched two popular new services – spaCy Tailored Pipelines and spaCy Tailored Analysis. Happy reading! New spaCy pipeline components As part of our spaCy v3.3

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Efficient continual pre-training LLMs for financial domains

AWS Machine Learning Blog

Large language models (LLMs) are generally trained on large publicly available datasets that are domain agnostic. For example, Meta’s Llama models are trained on datasets such as CommonCrawl , C4 , Wikipedia, and ArXiv. These datasets encompass a broad range of topics and domains.

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Explainability in AI and Machine Learning Systems: An Overview

Heartbeat

Source: ResearchGate Explainability refers to the ability to understand and evaluate the decisions and reasoning underlying the predictions from AI models (Castillo, 2021). This guide will buttress explainability in machine learning and AI systems. What is Explainability?

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Meta-Learning: Learning to Learn in Machine Learning

Heartbeat

Photo by Brett Jordan on Unsplash In the ever-evolving landscape of artificial intelligence and machine learning, researchers and practitioners continuously seek to elevate the capabilities of intelligent systems. Among the myriad breakthroughs in this field, Meta-Learning is pushing the boundaries of machine learning.

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Differentially private clustering for large-scale datasets

Google Research AI blog

Posted by Vincent Cohen-Addad and Alessandro Epasto, Research Scientists, Google Research, Graph Mining team Clustering is a central problem in unsupervised machine learning (ML) with many applications across domains in both industry and academic research more broadly. a relationship in a social network).

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AI Engineers Salaries Across the Globe

Pickl AI

The AI engineers are responsible for designing, developing and deploying the AI models and systems. In this blog, we are going to take you through some of the key aspects associated with the profession of AI engineering and the best countries that offer excellent growth opportunities to such professionals. from 2021 to 2027.