Poetry Generation Based on LSTM

Poetry Generation Based on LSTM

Introduction The main content of this article is poetry generation based on LSTM, which includes an introduction to the dataset, experimental code, and results. The experiment uses a Long Short-Term Memory (LSTM) deep learning model, trained for 10 epochs. During the testing process, poetry generation results are produced at each epoch, and as the epochs … Read more

The Era of Transformers: Why LSTM Models Still Matter

The Era of Transformers: Why LSTM Models Still Matter

Follow us on WeChat “ML_NLP” Set as “Starred” for heavy content delivered first-hand! Source | Zhihu Author | DengBoCong Link | https://www.zhihu.com/question/439243827/answer/1685085848 Editor | Machine Learning Algorithms and Natural Language Processing WeChat Account This article is for academic sharing. If there is an infringement, please contact us to delete it. I wrote a lot specifically … Read more

A Comprehensive Guide to LSTM in Machine Learning

A Comprehensive Guide to LSTM in Machine Learning

LSTM is a type of time-recursive neural network suitable for processing and predicting important events with relatively long intervals and delays in time series. It has achieved excellent results in a series of applications such as natural language processing and language recognition. “Long Short Term Memory Networks with Python” is a book by Australian machine … Read more

Why LSTM Is So Effective?

Why LSTM Is So Effective?

Follow the public account “ML_NLP“ Set as “Starred“, heavy content delivered first time! From | Zhihu Address | https://www.zhihu.com/question/278825804/answer/402634502 Author | Tian Yu Su Editor | Machine Learning Algorithms and Natural Language Processing Public Account This article is for academic sharing only. If there is an infringement, please contact the background for deletion. I have … Read more

Understanding LSTM – Long Short Term Memory Networks

Understanding LSTM - Long Short Term Memory Networks

Recurrent Neural Networks (RNN) People do not start thinking from scratch every second, just as you do not relearn every word while reading this article; human thinking has continuity. Traditional Convolutional Neural Networks lack memory and cannot solve this problem, while Recurrent Neural Networks (RNNs) can address this issue. In RNNs, the cycle allows for … Read more

Step-by-Step Guide to Understanding LSTM

Step-by-Step Guide to Understanding LSTM

Click on the above “Visual Learning for Beginners“, select to add to favorites or pin. Important content delivered in real-time 1. What is LSTM LSTM stands for Long Short-Term Memory, a type of recurrent neural network (RNN) that can handle sequential data and is widely used in fields such as natural language processing and speech … Read more

Why LSTMs Are So Effective? Five Secrets You Should Know

Why LSTMs Are So Effective? Five Secrets You Should Know

Long Short-Term Memory networks (LSTM), as an improved version of Recurrent Neural Networks (RNN), not only solve the problem of RNNs being unable to handle long-distance dependencies but also address common issues in neural networks such as gradient explosion or gradient vanishing, making them very effective in processing sequential data. What are the fundamental reasons … Read more

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

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

Understanding Transformer Principles and Their Applications in CV

Understanding Transformer Principles and Their Applications in CV

Currently, there are applications based on Transformer in three major image problems:Classification (ViT), Detection (DETR) and Segmentation (SETR), all achieving good results. In the future, could Transformer possibly replace CNN? Will Transformer revolutionize the CV field just like its application in NLP? What might the research directions be? Please look forward to the next article … Read more

Deep Learning Methods for NLP Text Classification

Deep Learning Methods for NLP Text Classification

Li Dakang1 minute ago 1. The purpose of this library is to explore methods for NLP text classification using deep learning. 2. It has various benchmark models for text classification. 3. It also supports multi-label classification, where multiple labels are associated with sentences or documents. Although many of these models are quite simple and may … Read more