Remove Convolutional Neural Networks Remove Deep Learning Remove Natural Language Processing
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Transfer Learning for NLP: Fine-Tuning BERT for Text Classification

Analytics Vidhya

Introduction With the advancement in deep learning, neural network architectures like recurrent neural networks (RNN and LSTM) and convolutional neural networks (CNN) have shown.

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Natural Language Processing Using CNNs for Sentence Classification

Analytics Vidhya

The post Natural Language Processing Using CNNs for Sentence Classification appeared first on Analytics Vidhya. A sentence is classified into a class in sentence classification. A question database will be used for this article and […].

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Deep Learning Architectures From CNN, RNN, GAN, and Transformers To Encoder-Decoder Architectures

Marktechpost

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models.

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Is Traditional Machine Learning Still Relevant?

Unite.AI

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

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AI News Weekly - Issue #343: Summer Fiction Reads about AI - Jul 27th 2023

AI Weekly

techcrunch.com The Essential Artificial Intelligence Glossary for Marketers (90+ Terms) BERT - Bidirectional Encoder Representations from Transformers (BERT) is Google’s deep learning model designed explicitly for natural language processing tasks like answering questions, analyzing sentiment, and translation.

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AI News Weekly - Issue #356: DeepMind's Take: AI Risk = Climate Crisis? - Oct 26th 2023

AI Weekly

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics.

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A Guide to Convolutional Neural Networks

Heartbeat

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs learn geometric properties on different scales by applying convolutional filters to input data.