You may be familiar with reinforcement learning, and you may also know about RNNs. What sparks can these two relatively complex concepts in the world of machine learning create together? Let me share a few thoughts. Before discussing RNNs, let’s first talk about reinforcement learning. Reinforcement learning is gaining increasing attention; its importance can be … Read more
↑↑↑ Follow for “Star Mark“Kaggle Competition Guide Kaggle Competition Guide Author: Fareise, excerpted from Yuan Yuan’s Algorithm Notes Using RNN for Long-Term Time Series Forecasting, Is It Better Than Transformer SOTA? This article introduced today comes from South China University of Technology, proposing an RNN-based long-term time series forecasting model that outperforms the SOTA Transformer … 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
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
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
Over 200 star enterprises and 20 top investors from renowned investment institutions participated! “New Intelligence Growth List” aims to discover innovative companies in the AI field with “tenfold growth in three years“, will the next wave of AI unicorns include you? Click read the original text for details! According to Lei Feng Network: Artificial intelligence … Read more
Introduction: Hello, readers of the “Beginner’s Data Learning” series! It has been a while. Google recently launched a neural network visualization teaching platform called “TensorFlow Playground”. You can now play with neural networks right in your browser! Isn’t that amazing? After trying it out with the beginner, you’ll definitely feel like, “Aha, this is what … Read more
1 Introduction Deep neural networks are composed of neurons organized into layers and interconnected, capturing their architecture through computation graphs, where neurons are represented as nodes and directed edges connect different layers of neurons. The performance of neural networks depends on their architecture, but there is currently a lack of systematic understanding of the relationship … Read more
Produced by Big Data Digest Compiled by: Shijin Tian, Ni Ni, Hu Jia, Yun Zhou In many machine learning labs, machines have undergone thousands of hours of training. During this process, researchers often take many detours and fix many bugs, but it is certain that the experience and knowledge gained during the research process are … Read more
Reported by New Intelligence Editor: LRS [New Intelligence Overview] It has almost become a consensus that bigger neural networks are better, but this idea contradicts traditional function fitting theory. Recently, researchers from Microsoft published a paper at NeurIPS proving the necessity of large-scale neural networks mathematically, suggesting they should be even larger than expected. As … Read more