Bi-RNN

How to Input Variable Length Sequences as a Batch to RNN in Pytorch

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How to Input Variable Length Sequences as a Batch to RNN in Pytorch

Follow the official account “ML_NLP“ Set as “Starred“, delivering heavy content immediately! Source | Zhihu Address | https://zhuanlan.zhihu.com/p/97378498 Author | Si Jie’s Portable Mattress Editor | Machine Learning Algorithms and Natural Language Processing Official Account This article is authorized by the author, secondary reproduction is prohibited Modules and functions needed: import torch import torch.nn as … Read more

Current Research Status and Development Trends of Intelligent Tool Wear Monitoring Methods

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Current Research Status and Development Trends of Intelligent Tool Wear Monitoring Methods

Editor’s Note The real-time monitoring of tool wear during machining is of significant importance for reducing equipment downtime and lowering costs caused by tool wear. Traditional tool wear monitoring methods based on signal processing and shallow learning models require manual extraction of lengthy features, which cannot achieve intelligent monitoring. To overcome this inherent limitation, deep … Read more

How Deep Learning Models Handle Variable Size Inputs

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How Deep Learning Models Handle Variable Size Inputs

MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP graduate students, university professors, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning, especially for beginners. Reprinted from | … Read more

Automatically Generate Ancient Poetry Based on RNN

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Automatically Generate Ancient Poetry Based on RNN

Column ❈ Author: yonggege, author of Python Chinese community column GitHub Address: https://github.com/wzyonggege ❈ 0. char-rnn There are already many introductions about RNN, LSTM, and GRU. The char-rnn is a multi-layer RNN network. This time, we will use the Tensorflow version of sherjilozair/char-rnn-tensorflow to input a large number of ancient poems and let the machine … Read more

Online Handwritten Chinese Character Recognition Using New RNN Architecture

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Online Handwritten Chinese Character Recognition Using New RNN Architecture

This article briefly introduces the main work of the paper accepted in April 2019 by Pattern Recognition titled “Recognizing Online Handwritten Chinese Characters Using RNNs with New Computing Architectures”. This paper mainly addresses the end-to-end recognition problem of handwritten Chinese characters. 1. Research Background Handwritten input is a very common human-computer interaction method. With the … Read more

Simple RNN Time Series Prediction

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Simple RNN Time Series Prediction

This article will introduce the use of a simple RNN model for time series prediction. For example, we currently have a segment of a sine curve as shown in the figure below. We will input the red part and train the model to output the next segment’s values. First, let’s analyze it. Assuming we input … Read more

Understanding LSTMs: Long Short-Term Memory Networks

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Understanding LSTMs: Long Short-Term Memory Networks

In the previous article, we summarized RNNs (Recurrent Neural Networks). Due to the gradient vanishing problem in RNNs, it is challenging to handle long sequences of data. Experts have improved RNNs, resulting in a special case called LSTM (Long Short-Term Memory), which can avoid the gradient vanishing problem typical of conventional RNNs, thus gaining widespread … Read more

Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 2)

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Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 2)

For More Content, Please Follow: Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 1) Andrew Ng: Deep Learning Knowledge Explained in 28 Images (Part 2) 23-24 Basics of Recurrent Neural Networks As shown above, sequence problems such as named entity recognition account for a significant proportion of real-life applications, while traditional machine learning … Read more

Transformer, CNN, GNN, RNN: Understanding Attention Mechanisms

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Transformer, CNN, GNN, RNN: Understanding Attention Mechanisms

Follow the official account “ML_NLP“ Set as “Starred“, essential resources delivered first-hand! Looking back at the phrase from 2017, “Attention is all you need”, it truly was a prophetic statement. The Transformer model started with machine translation in natural language processing, gradually influencing the field (I was still using LSTM in my graduation thesis in … Read more

Implementing Recurrent Neural Networks (RNNs) in Python for Time Series Prediction

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Implementing Recurrent Neural Networks (RNNs) in Python for Time Series Prediction

Case Introduction This case will demonstrate how to use Recurrent Neural Networks (RNNs) for time series prediction. Specifically, we will use RNNs to predict the future values of a variable that depends on its own historical values. In this case, we will use a temperature dataset. We will provide the temperature values from the past … Read more