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From Rulesets to Transformers: A Journey Through the Evolution of SOTA in NLP

Mlearning.ai

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

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Top 6 Kubernetes use cases

IBM Journey to AI blog

Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).

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Deep Learning for NLP: Word2Vec, Doc2Vec, and Top2Vec Demystified

Mlearning.ai

NLP A Comprehensive Guide to Word2Vec, Doc2Vec, and Top2Vec for Natural Language Processing In recent years, the field of natural language processing (NLP) has seen tremendous growth, and one of the most significant developments has been the advent of word embedding techniques.

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Against LLM maximalism

Explosion

A lot of people are building truly new things with Large Language Models (LLMs), like wild interactive fiction experiences that weren’t possible before. But if you’re working on the same sort of Natural Language Processing (NLP) problems that businesses have been trying to solve for a long time, what’s the best way to use them?

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10 takeaways from 10 years of data science for social good

DrivenData Labs

Looking back ¶ When we started DrivenData in 2014, the application of data science for social good was in its infancy. The startup cost is now lower to deploy everything from a GPU-enabled virtual machine for a one-off experiment to a scalable cluster for real-time model execution.

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Introducing spaCy

Explosion

spaCy is a new library for text processing in Python and Cython. I wrote it because I think small companies are terrible at natural language processing (NLP). This is easy to do, as spaCy loads a vector-space representation for every word (by default, the vectors produced by Levy and Goldberg (2014) _).

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Robustness of a Markov Blanket Discovery Approach to Adversarial Attack in Image Segmentation: An…

Mlearning.ai

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., Generative adversarial networks-based adversarial training for natural language processing. 2012; Otsu, 1979; Long et al., 2013; Goodfellow et al.,