AWS Machine Learning Blog

OCTOBER 23, 2023

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Founded in 2011, Talent.com is one of the world’s largest sources of employment. It’s designed to significantly speed up deep learning model training. The model is replicated on every GPU.

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IBM Journey to AI blog

OCTOBER 12, 2023

In other words, traditional machine learning models need human intervention to process new information and perform any new task that falls outside their initial training. For example, Apple made Siri a feature of its iOS in 2011. Human intervention was required to expand Siri’s knowledge base and functionality.

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AWS Machine Learning Blog

SEPTEMBER 9, 2024

As LLMs have grown larger, their performance on a wide range of natural language processing tasks has also improved significantly, but the increased size of LLMs has led to significant computational and resource challenges. degree in Computer Science in 2011 from the University of Lille 1. He holds a M.E.

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Deep Learning ML Machine Learning Natural Language Processing 100

AWS Machine Learning Blog

DECEMBER 14, 2023

This post is co-authored by Anatoly Khomenko, Machine Learning Engineer, and Abdenour Bezzouh, Chief Technology Officer at Talent.com. Established in 2011, Talent.com aggregates paid job listings from their clients and public job listings, and has created a unified, easily searchable platform.

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Sebastian Ruder

NOVEMBER 14, 2022

Developing models that work for more languages is important in order to offset the existing language divide and to ensure that speakers of non-English languages are not left behind, among many other reasons. This post is partially based on a keynote I gave at the Deep Learning Indaba 2022. Kolesnikov, A.,

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Natural Language Processing NLP Computational Linguistics BERT 52

Lexalytics

APRIL 5, 2021

They were not wrong: the results they found about the limitations of perceptrons still apply even to the more sophisticated deep-learning networks of today. And indeed we can see other machine learning topics arising to take their place, like “optimization” in the mid-’00s, with “deep learning” springing out of nowhere in 2012.

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Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Explosion

FEBRUARY 12, 2017

In this post, I’ll explain how to solve text-pair tasks with deep learning, using both new and established tips and technologies. The Quora dataset is an example of an important type of Natural Language Processing problem: text-pair classification. This data set is large, real, and relevant — a rare combination.

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Neural Network Deep Learning Natural Language Processing NLP 40

Explosion

MARCH 17, 2019

of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. spaCy is an open-source library for industrial-strength natural language processing in Python. Version 2.1 Prodigy is a fully scriptable annotation tool that complements spaCy extremely well.

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NLP Python Neural Network Natural Language Processing 52

ML Review

MAY 3, 2018

Recent Intersections Between Computer Vision and Natural Language Processing (Part One) This is the first instalment of our latest publication series looking at some of the intersections between Computer Vision (CV) and Natural Language Processing (NLP). Thanks for reading!

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