Remove Categorization Remove Deep Learning Remove NLP
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Accelerating scope 3 emissions accounting: LLMs to the rescue

IBM Journey to AI blog

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

ESG 238
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ProtEx: Enhancing Protein Function Prediction with Retrieval-Augmented Deep Learning

Marktechpost

Functions are categorized using ontologies like Gene Ontology (GO) terms, Enzyme Commission (EC) numbers, and Pfam families. Techniques include homology-based methods, which use sequence alignment tools like BLAST to infer function, and deep learning methods, which predict functions directly from sequences.

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20 GitHub Repositories to Master Natural Language Processing (NLP)

Marktechpost

Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. As NLP continues to advance, there is a growing need for skilled professionals to develop innovative solutions for various applications, such as chatbots, sentiment analysis, and machine translation.

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10 Best AI Email Inbox Management Tools (June 2023)

Unite.AI

Based on this, it makes an educated guess about the importance of incoming emails, and categorizes them into specific folders. In addition to the smart categorization of emails, SaneBox also comes with a feature named SaneBlackHole, designed to banish unwanted emails.

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AI and Blockchain Integration for Preserving Privacy

Unite.AI

Blockchain technology can be categorized primarily on the basis of the level of accessibility and control they offer, with Public, Private, and Federated being the three main types of blockchain technologies. Deep learning frameworks can be classified into two categories: Supervised learning, and Unsupervised learning.

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Deep Learning Approaches to Sentiment Analysis (with spaCy!)

ODSC - Open Data Science

Be sure to check out his talk, “ Bagging to BERT — A Tour of Applied NLP ,” there! If a Natural Language Processing (NLP) system does not have that context, we’d expect it not to get the joke. In this post, I’ll be demonstrating two deep learning approaches to sentiment analysis. deep” architecture).

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

Unite.AI

With nine times the speed of the Nvidia A100, these GPUs excel in handling deep learning workloads. This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction.