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transfer-learning-fault-diagnosis-pytorch

A transfer learning fault diagnosis repository covering popular algorithms

transferlearning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

transformer-time-series-prediction

proof of concept for a transformer-based time series prediction model

transformer_time_series

Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting (NeurIPS 2019)

ts_anomaly_detection_course

examples for timeseries anomaly detection for course

tsad

Package for Time Series Forecasting and Anomaly Detection Problems.

tsaug

A Python package for time series augmentation

tscv

Time Series Cross-Validation -- an extension for scikit-learn

tsfel

An intuitive library to extract features from time series.

tsfresh

Automatic extraction of relevant features from time series:

tsmoothie

A python library for time-series smoothing and outlier detection in a vectorized way.

tsod

Anomaly Detection for time series data

tspiral

A python package for time series forecasting with scikit-learn estimators.

tutorials_and_presentations

There are all my tutorials and presentations from Python or Data Science events

upgini

Free automated data enrichment library for machine learning → searches through thousands of ready-to-use features from public and community shared data sources

upscayl

🆙 Upscayl - Free and Open Source AI Image Upscaler for Linux, MacOS and Windows built with Linux-First philosophy.

usad

use-classes-for-generating-signals

Learn how to build a class in python and use it to generate signals

vae-lstm-for-anomaly-detection

We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

vae_anomaly_detection

vecstack

Python package for stacking (machine learning technique)

verstack

vibration-based-fault-diagnosis-with-low-delay

Python codes “Jupyter notebooks” for the paper entitled "A Hybrid Method for Condition Monitoring and Fault Diagnosis of Rolling Bearings With Low System Delay, IEEE Trans. on Instrumentation and Measurement, Aug. 2022. Techniques used: Wavelet Packet Transform (WPT) & Fast Fourier Transform (FFT). Application: vibration-based fault diagnosis.

vscode_exp_tracking_with_dvc

An example of turning VS code into an experiment tracking platform

waterfall

An easy to use waterfall chart function for Python

whylogs-examples

some whylogs v1 profile visualizer examples to test, learn, and demo

xam

:dart: Personal data science and machine learning toolbox

xgbfi

XGBoost Feature Interactions & Importance

xgbfir

XGBoost Feature Interactions Reshaped

xgboostlss

An extension of XGBoost to probabilistic modelling and prediction