The hands-on deep learning live course has completed the first three parts! In the past 4 months, Dr. Mu Li, a senior chief scientist at Amazon has explained the basics of deep learning, convolutional neural networks, and computer vision. Since the course started, over 10,000 people have participated in the live learning, and the course … Read more
Author: David9 Address: http://nooverfit.com/ Named Entity Recognition (NER) is an important topic in semantic understanding. NER is like object detection in the field of natural language. Finding noun entities in document D is not enough; in many cases, we need to understand whether this noun represents a location, person, or organization, etc.: The above figure … Read more
RWKV Submitted by QbitAI | WeChat Official Account Not following the usual path of Transformers, the domestically modified RNN architecture RWKV has made new progress: Two new RWKV architectures have been proposed, namely Eagle (RWKV-5) and Finch (RWKV-6). These two sequence models are based on the RWKV-4 architecture and have been improved. The advancements in … Read more
Machine Heart Report Contributor: Siyuan With the popularity of frameworks like TensorFlow and PyTorch, building neural networks often just involves calling a few API lines. Most developers have become unfamiliar with the underlying mechanisms, especially how to implement neural networks using pure NumPy. Previously, Machine Heart introduced how to implement a simple convolutional neural network … Read more
MLNLP ( Machine Learning Algorithms and Natural Language Processing ) community is a well-known natural language processing community both domestically and internationally, covering NLP graduate students, university teachers, and corporate researchers. The vision of the community is to promote communication between the academic and industrial circles of natural language processing and machine learning, as well … Read more
Selected from arXiv Authors: Matthew MacKay et al. Translated by: Machine Heart Contributors: Gao Xuan, Zhang Qian Recurrent Neural Networks (RNNs) achieve the best current performance in processing sequential data, but they require a large amount of memory during training. Reversible Recurrent Neural Networks provide a way to reduce the memory requirements for training, as … Read more
Source | Zhihu Author | JerryFly Link | https://zhuanlan.zhihu.com/p/115823190 Editor | Deep Learning Matters WeChat Official Account This article is for academic exchange only. If there is any infringement, please contact us for deletion. RNN is commonly used to handle sequential problems. This article demonstrates the computation process of RNN using animated graphics. The three … Read more
“Programming is the art of telling another human being what one wants the computer to do.” — Donald Knuth 📑Paper:A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond 🔧GitHub:https://github.com/QiushiSun/NCISurvey Note: The authors of the paper are from Shanghai Artificial Intelligence Laboratory, The University of Hong Kong, National University of Singapore, East China Normal University, … Read more
Produced by Big Data Digest Compiled by: Xiao Qi, Mixed Sweet, Xia Yawei Trump’s new re-election campaign has begun. The author’s interest in Trump’s distinctive language style raises the question: can a speech that embodies his style be generated using a Recurrent Neural Network (RNN) trained on his tweets and speeches? The conclusion is that … Read more
Click the above“Machine Learning and Generative Adversarial Networks” to follow and star Get interesting and fun cutting-edge content! Author on Zhihu: Mr. Good Good, please delete if infringing https://zhuanlan.zhihu.com/p/361893386 1 Background Knowledge The Attention mechanism was first proposed in the field of visual images, probably in the 1990s, but it really gained popularity with the … Read more