AWS Machine Learning Blog

SEPTEMBER 11, 2024

This is accomplished by breaking the problem into independent parts so that each processing element can complete its part of the workload algorithm simultaneously. Parallelism is suited for workloads that are repetitive, fixed tasks, involving little conditional branching and often large amounts of data.

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ML Deep Learning Algorithm Large Language Models 91

Topbots

JUNE 22, 2023

Outperforming algorithmic trading reinforcement learning systems: A supervised approach to the cryptocurrency market. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, pages 595–605. ALLDATA, The Second Inter-national Conference on Big Data, Small Data, Linked Data and Open Data (2016).

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Machine Learning ChatGPT Natural Language Processing Categorization 111

NLP People

APRIL 2, 2018

Here you can find a free lecture entitled Deep Learning: A Revolution in Artificial Intelligence, which took place on the 4th of February 2016 and was presented by AI expert Yann LeCun. It’s presented at both the Nice Sophia-Antipolis and Paris campuses of the Data ScienceTech Institute. And, sometimes they’re hiring.

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NLP Data Mining Natural Language Processing Machine Learning 52

Dlabs.ai

FEBRUARY 10, 2020

Elsewhere, complex AI algorithms can help finance and accounting professionals carry out their day jobs, reducing manual work so they can focus on more important tasks — freeing headspace to not only minimize error rate but to improve efficiencies as well. We can’t hide from the fact: fatigue and stress contribute to many accidents.

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Artificial Intelligence Artificial Intelligence Machine Learning Algorithm 52

Lexalytics

APRIL 5, 2021

This would change in 1986 with the publication of “Parallel Distributed Processing” [ 6 ], which included a description of the backpropagation algorithm [ 7 ]. In retrospect, this algorithm seems obvious, and perhaps it was. We were definitely in a Kuhnian pre-paradigmatic period. It would not be the last time that happened.)

Neural Network 52

Neural Network Convolutional Neural Networks Natural Language Processing BERT 52

Unite.AI

NOVEMBER 28, 2024

1980s – The Rise of Machine Learning The 1980s introduced significant advances in machine learning , enabling AI systems to learn and make decisions from data. The invention of the backpropagation algorithm in 1986 allowed neural networks to improve by learning from errors.

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Robotics Algorithm AI AI 284

AI News

JUNE 8, 2023

McKinsey, a global consulting firm, predicts that between 2016 and 2030, AI-related advancements could impact approximately 15 percent of the global workforce, potentially displacing 400 million workers worldwide. Check out AI & Big Data Expo taking place in Amsterdam, California, and London.

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Artificial Intelligence Artificial Intelligence Big Data Software Engineer 326

Towards AI

MAY 1, 2024

The Role of AI and Algorithms in Social Media In today’s fast-paced world, social media has become more than just a digital landscape. A Brief History of Algorithms and Their Increasing Use Cases in Social Media ‘An algorithm is a series of instructions designed to solve specific problems, perform tasks or make decisions’ [2].

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Algorithm AI AI Big Data 97

Mlearning.ai

FEBRUARY 10, 2023

Back in 2016 I was trying to explain to software engineers how to think about machine learning models from a software design perspective; I told them that they should think of a database. Both serve as a means of storing representations of historical data, which can later be queried. Library, primitive data storage solution.

Neural Network 52

Neural Network ChatGPT Big Data Software Engineer 52

Unite.AI

MAY 27, 2023

The power of AI-driven data analytics became evident in the 2012 and 2016 US election campaigns. In 2012, Obama's team used AI and big data to innovate voter targeting. In 2016, Trump's team used it to identify specific voter segments and tailor outreach strategies.

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Generative AI Chatbots AI AI 217