Text Generation with LSTM Based on Anna Karenina

Text Generation with LSTM Based on Anna Karenina

Click the “MLNLP” above to select the “Starred” public account. Heavyweight content delivered promptly. Author: Tian Yu Su https://zhuanlan.zhihu.com/p/27087310 Introduction Recently, I finished reading some foreign materials on LSTM, mainly referencing Colah’s blog and Andrej Karpathy’s blog on RNN and LSTM, and I am preparing to implement an LSTM model. The basic framework of the … Read more

Understanding LSTM Neural Networks

Understanding LSTM Neural Networks

Recurrent Neural Networks In traditional neural networks, the model does not pay attention to what information from the previous moment can be used for the next moment; it only focuses on the current moment’s processing. For example, if we want to classify the events that occur at each moment in a movie, knowing the events … 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

Understanding LSTM and GRU in Gated Recurrent Neural Networks

Understanding LSTM and GRU in Gated Recurrent Neural Networks

Click on the above “Beginner’s Guide to Visual Learning” to choose to add “Star” or “Top” Heavyweight content delivered at the first time Editor | Anke Produced by | Panchuang AI Technology Team Table of Contents: Introduction to Gated Recurrent Neural Networks Long Short-Term Memory Networks (LSTM) Gated Recurrent Units (GRU) Implementing LSTM and GRU … 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

Understanding Long Short-Term Memory Networks (LSTM)

Understanding Long Short-Term Memory Networks (LSTM)

Written by丨Zhang Tianrong He is not the first person to endow neural networks with “memory,” but the long short-term memory network (LSTM) he invented has provided neural networks with longer and practically useful memory. LSTM has long been used by Google, Apple, Amazon, Facebook, etc., to implement functions such as speech recognition and translation. Today, … Read more