Remove 2014 Remove Deep Learning Remove Natural Language Processing
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Deep Learning Approaches to Sentiment Analysis (with spaCy!)

ODSC - Open Data Science

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 learning refers to the use of neural network architectures, characterized by their multi-layer design (i.e.

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Alien contact: Harvard professor foresees AI as first point of communication

Dataconomy

million ocean expedition to search for the remains of an object that purportedly crashed into the water in 2014. In 2019, Israeli astronomer Loeb and his co-author Amir Siraj came to the conclusion that in 2014, Earth was struck by a body coming from outside our solar system.

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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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Getting Started with AI

Towards AI

Machine learning (ML) is a subset of AI that provides computer systems the ability to automatically learn and improve from experience without being explicitly programmed. Deep learning (DL) is a subset of machine learning that uses neural networks which have a structure similar to the human neural system.

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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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7 Generative AI trends to watch out for in 2024

How to Learn Machine Learning

It falls under machine learning and uses deep learning algorithms and programs to create music, art, and other creative content based on the user’s input. However, significant strides were made in 2014 when Lan Goodfellow and his team introduced Generative adversarial networks (GANs).

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A Guide to Convolutional Neural Networks

Heartbeat

AlexNet significantly improved performance over previous approaches and helped popularize deep learning and CNNs. GoogLeNet: is a highly optimized CNN architecture developed by researchers at Google in 2014. VGG-16: does the Visual Geometry Group develop an intense CNN architecture at the University of Oxford?