First, I recommend a Jupyter environment, which is provided by Google called colab (https://colab.research.google.com/), where you can use free GPUs. The first time you use it, you need to download the relevant Python libraries in the experimental environment. !pip install torch!pip install torchtext!python -m spacy download en Our preliminary idea is to first input a … Read more
Author: Sharmistha Chatterjee Translator: Chen Zhiyan Proofreader: Wu Jindi This article is approximately 5500 words, and it is recommended to read for 10+ minutes. This article discusses issues related to ensemble learning with simple ARIMA/SARIMA and LSTM time series. Sharmistha Chatterjee https://towardsdatascience.com/@sharmi.chatterjee Motivation The five most commonly used time series models in traditional time series … Read more
Today, I would like to introduce a powerful deep learning model: CNN-LSTM-Attention! This model combines three different types of neural network architectures, fully exploiting the spatial and temporal information in the data. It not only captures the local features and long-term dependencies of the data but also automatically focuses on the most important parts of … Read more
Case Introduction This case will demonstrate how to use Long Short-Term Memory (LSTM) to predict Boston housing prices. We will utilize the LSTM model from the Keras library to accomplish this task. By using historical housing price data, we will train the LSTM model to predict future housing prices. Algorithm Principles Long Short-Term Memory (LSTM) … Read more
Source: Big Data Mining DT Data Analysis This article is 1500 words, suggested reading time 5 minutes. This article introduces the principles of LSTM networks and their application in the pop music trend prediction competition. Reply with the keyword“music” to download the complete code and dataset 1. Principles of LSTM Networks 1.1 Key Points LSTM … Read more
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
Hello everyone, I am Orange Brother! Today, we will look at how to use the LSTM model for stock price prediction and achieve automated trading through the Alpaca API. This code is mainly divided into the following key parts: importing necessary libraries, data preparation, model construction, model training, model loading and evaluation, and automated trading … Read more
Article Number | 1009-265X(2020)06-0055-07 Source | “Modern Textile Technology” 2020 Issue 6 Authors | Wang Jingjing a, Chen Minzhi b (Zhejiang University of Science and Technology, a. School of Clothing; b. International Education College, Hangzhou) Author Introduction | Wang Jingjing (1993-), female, from Nanyang, Henan, master’s student, mainly engaged in research in clothing technology and … Read more
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
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