♚ Author: Yishui Hancheng, CSDN Blog Expert, Research Directions: Machine Learning, Deep Learning, NLP, CV Blog: http://yishuihancheng.blog.csdn.net This article mainly practices multivariate sequence prediction based on LSTM (Long Short-Term Memory) neural networks, completing the prediction, analysis, and visualization of data at specified future time steps, and teaches you step by step how to build your … Read more
Author: Jaime Zornoza, Technical University of Madrid Translation: Chen Zhiyan Proofreading: Wang Weili This article is approximately 3700 words, and it is recommended to read in 10+ minutes. This article will help you understand deep learning neural networks in a way never seen before, and build a Chatbot using NLP! Have you ever fantasized about … Read more
Sharing a paper on video super-resolution titled Revisiting Temporal Modeling for Video Super-resolution, which is a BMVC 2020 paper. The results of this paper currently rank first on several datasets for video super-resolution, and the code has been open-sourced. Affiliations: Tsinghua University, New York University, Huawei Noah’s Ark Lab 1 Highlights This paper proposes a … Read more
Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, I felt enlightened. This article … Read more
Originally from Python AI Frontiers This article systematically and comprehensively organizes the introduction and algorithm principles of various deep learning models. 1 Main Text Deep learning methods utilize neural network models for advanced pattern recognition and automatic feature extraction, achieving significant results in the field of data mining in recent years. Common models include not … Read more
Source: Machine Learning Algorithms Explained Friends familiar with deep learning know that LSTM is a type of RNN model that can conveniently handle time series data and is widely used in fields such as NLP. After watching Professor Li Hongyi’s deep learning videos from National Taiwan University, especially the first part introducing RNN and LSTM, … Read more
Click the “MLNLP” above and select “Star” for the public account Heavy content delivered first-hand Author | Yi Zhen Address | https://zhuanlan.zhihu.com/p/30844905 Column | Machine Learning Algorithms and Natural Language Processing Understanding RNN (Recurrent Neural Networks) Basics Basics of Neural Networks Neural networks can be considered as black boxes that can fit any function. As … Read more
Click on the above “Visual Learning for Beginners” to choose to add a Star or “Pin” Heavyweight content delivered first-hand From | Zhihu Author | Lucas Link | https://zhuanlan.zhihu.com/p/85995376 Understanding RNN: Recurrent Neural Networks and Their PyTorch Implementation Recurrent Neural Networks (RNN) are a type of neural network with short-term memory capabilities. Specifically, the network … Read more
Click the above“Beginner’s Guide to Vision” to choose to add Starred or “Top” Essential Knowledge Delivered First-Hand 1. Introduction to CNN CNN is a type of neural network that utilizes convolutional calculations. It can preserve the main features of a large image by reducing it to a smaller pixel image through convolutional calculations. This article … Read more
1 Algorithm History In 1986, Elman and others proposed the Recurrent Neural Network for processing sequential data. Just as Convolutional Neural Networks are specifically designed for processing two-dimensional data (such as images), Recurrent Neural Networks are specialized for handling sequential information. Recurrent networks can be extended to longer sequences, and most recurrent neural networks can … Read more