Transfer Learning

In-Depth Explanation of Adapter Techniques in NLP

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In-Depth Explanation of Adapter Techniques in NLP

MLNLP ( Machine Learning Algorithms and Natural Language Processing ) community is a well-known natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The vision of the community is to promote communication between academia, industry, and enthusiasts in natural language processing and machine learning, especially … Read more

In-Depth Explanation of Adapter Technology in NLP

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In-Depth Explanation of Adapter Technology in NLP

Delivering NLP technical insights to you daily! © Author | Wu Di Institution | UCLA Research Direction | NLP Typesetting | PaperWeekly Introduction In modern natural language processing (NLP) applications, using pre-trained representations for transfer learning is an important method. After deep learning began to be applied, transfer learning first appeared in the use of … Read more

Future Research Directions of NLP in Marketing

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Article Title: Natural Language Processing in Marketing Authors: Jochen Hartmann, Oded Netzer Published Journal: Artificial Intelligence in Marketing Review of Marketing Research Article Summary: Introduce the applications of natural language processing (NLP) in marketing, review traditional NLP methods, look ahead to the future applications of embedding-based methods, pre-trained language models and transfer learning in marketing, … Read more

10 TensorFlow 2.x Tips for Efficient Usage

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10 TensorFlow 2.x Tips for Efficient Usage

Click on the above “Beginner Learning Vision”, choose to add Star or Top ” Important content delivered at the first time Author | Rohan Jagtap Compiled by | ronghuaiyang Source | AI Park TensorFlow 2.x provides a lot of simplicity in building models and the overall use of TensorFlow. In this article, we will explore … Read more

Image Classification Techniques: KNN, SVM, BP Neural Networks, CNN, and Transfer Learning

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Image Classification Techniques: KNN, SVM, BP Neural Networks, CNN, and Transfer Learning

Original: Medium Author: Shiyu Mou Source: Robot Circle This article has a length of 4600 words and is suggested to be read in 6 minutes. This article introduces you to 5 techniques for image classification, summarizes and consolidates algorithms, implementation methods, and conducts experimental validation. The image classification problem is the task of assigning labels … Read more

40 Classic Papers on Convolutional Neural Networks

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40 Classic Papers on Convolutional Neural Networks

Reprinted from: Jishi Platform As one of the representative algorithms of deep learning, Convolutional Neural Networks (CNN) have achieved the best results in fields such as computer vision. In 1998, Yann LeCun proposed LeNet-5, applying the BP algorithm to train the neural network structure, forming the prototype of contemporary CNNs. In 2012, during the ImageNet … Read more

How to Achieve Broad AI? Insights from Sepp Hochreiter

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How to Achieve Broad AI? Insights from Sepp Hochreiter

Reprinted from AI Technology Review Human intelligence, encompassing consciousness, cognition, decision-making, and more, seems to have captivated philosophers since the dawn of recorded history. Similarly, since the birth of AI, scientists have been pondering: How can AI achieve human-like intelligence? Recently, Professor Sepp Hochreiter, one of the founders of LSTM and the founder of the … Read more

Image Recognition Method for Wolframite Based on Deep Learning

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Image Recognition Method for Wolframite Based on Deep Learning

2020 “High Download Papers in Chinese and English” Special Series In 2020, the “Journal of China Nonferrous Metals” published a total of 608 papers in both Chinese and English, some of which have shown significant influence. According to the China National Knowledge Infrastructure download data (as of March 3, 2021), the highest single paper download … Read more

Overview of Transformer Pre-trained Models in NLP

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Overview of Transformer Pre-trained Models in NLP

The revolution brought by the Transformer in the field of natural language processing (NLP) is beyond words. Recently, researchers from the Indian Institute of Technology and biomedical AI startup Nference.ai conducted a comprehensive investigation of Transformer-based pre-trained models in NLP and compiled the results into a review paper. This article will roughly translate and introduce … Read more

Comparison of Five Image Classification Methods: KNN, SVM, BPNN, CNN, and Transfer Learning

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Comparison of Five Image Classification Methods: KNN, SVM, BPNN, CNN, and Transfer Learning

Selected from | Medium Transferred from | Machine Heart Contributors | Jiang Siyuan, Huang Xiaotian, Wu Pan Image classification is one of the fundamental research topics in the field of artificial intelligence, and researchers have developed a large number of algorithms for image classification. Recently, Shiyu Mou published an article on Medium, comparing five methods … Read more