/mymachine-learning

This is a reository to share my studys in machine learning, data science & artificial intelligence

Primary LanguageJupyter Notebook

mymachine-learning————这是一个记录我的计算机学习过程的git文件夹

  • 2024/7/22 更新 -- 通过bs4,requests和re库实现的豆瓣电影网站爬虫 -- doubancrawl.py
  • 2024/7/23 更新 -- 通过re,requests 和pandas实现东方财富网股票数据的爬虫 -- 东方财富网股票爬虫.py
  • 2024/7/27 更新文件夹 stockforecasting -- 一个使用LSTM预测股票价格的项目
  • 2024/7/27 对stockforecasting文件夹下的文件进行了更新
  • 2024/7/31 更新 -- stockforecasting，添加了prodit-predic算法。
  • 2024/7/31 更新 -- Bearing-diagnostic，添加了模型以使用CWRU数据集分类10种故障类型。
  • 2024/8/1 更新 -- Bearing-diagnostic，添加了数据预处理和特征提取文件data_create_CWRU_FFT.ipynb，该文件对CWRU数据集进行快速傅里叶变换，然后进行包络谱分析，提取3个特征频率数据。
  • 2024/8/1 更新 -- Bearing-diagnostic，添加了文件model_train_FFT.ipynb，该文件在从CWRU数据集中提取的特征频率数据上训练机器学习模型。
  • 2024/8/28 更新 -- Bearing-diagnostic，添加了新的训练文件，将振幅数据首先转换为2D，在IMS和CWRU数据集上进行轴承故障诊断测试，整体表现获得了提升。
  • 2024/8/28 创建Bearing_rul_prediction文件夹，添加了demo文件，用于预测轴承的剩余寿命,并使用了一种准确且泛化性高的RUL标签生成方式。

Author's Note

  • Most of the files in this repository are written in Chinese. But if there is a need, I could translate them into English. (Anyway I would probably update the English version on my self in the future)
  • For code explanation, datasets and ideas sharing, please contact the author at ianwu0907@gmail.com.

mymachine-learning — This is a Git folder that documents my computer learning journey

  • 2024/7/22 Update -- A web crawler for Douban movie website implemented using bs4, requests, and re libraries -- doubancrawl.py
  • 2024/7/23 Update -- A web crawler for stock data from Eastmoney.net implemented using re, requests, and pandas -- Eastmoney Stock Crawler.py
  • 2024/7/27 Update to the repository stockforecasting -- A project that predicts stock prices using LSTM
  • 2024/7/27 Files under the stockforecasting repository have been updated
  • 2024/7/31 Update stockforecasting , added prodit-predic algorithm
  • 2024/7/31 Update Bearing_diagnostic , added maching-models to classify 10 types of faults with CWRU dataset.
  • 2024/8/1 Update Bearing_diagnostic , added data pre-processing and feature extraction file data_create_CWRU_FFT.ipynb, which performs fast-fourier transformation and then Envelope Spectrum Analysis on the CWRU dataset, extracting 3 feature frequency data.
  • 2024/8/1 Update Bearing_diagnostic , added file model_train_FFT.ipynb, which trains the machine-learning models on the feature frequency data extracted from the CWRU dataset.
  • 2024/8/28 Update Bearing_diagnostic, added new training file that transforms the amplitude data into 2D first and give a better overall performance on IMS and CWRU dataset bearing fault diagnostic tasks.
  • 2024/8/28 Create Bearing_rul_prediction repository, added demo file to predict the remaining useful life of bearings on different datasets with a special and robust RUL label generating technique.