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
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
Machine Heart Column This column is produced by Machine Heart SOTA! Model Resource Station, updated every Sunday on the Machine Heart public account. This column will review common tasks in natural language processing, computer vision, and other fields, and detail the classic models that have achieved SOTA on these tasks. Visit SOTA! Model Resource Station … 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
Machine Heart Compilation Author: Sander Dieleman Editor: Panda W Diffusion models are very popular, and their descriptions vary widely. In this article, a DeepMind research scientist provides a comprehensive analysis of the topic “What is a diffusion model?” If you’ve tried one of the most popular AI painting tools, Stable Diffusion, then you’ve already experienced … 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
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
Big Data Digest Production Source: Google Blog Compiled by: Mali The weather in spring can change faster than you can turn a page; one moment it’s sunny, the next moment there’s a raging storm. In fact, accurately predicting the weather weeks or even minutes in advance is a scientific challenge that has a broad impact … 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
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