Karthikbadari

line_profiler

Line-by-line profiling for Python

boruta_py

Python implementations of the Boruta all-relevant feature selection method.

KernelCPD_WindSCADA

Code and supplementary material complementing the WES-publication: "Change-point detection in wind turbine SCADA data for robust condition monitoring with normal behaviour models""

Metis

Metis is a learnware platform in the field of AIOps.

awesome-anomaly-detection

A curated list of awesome anomaly detection resources

ppscore

Predictive Power Score (PPS) in Python

scikit-learn

scikit-learn: machine learning in Python

OpenOA

This library provides a framework for assessing wind plant performance using operational assessment (OA) methodologies that consume time series data from wind plants. The goal of the project is to provide an open source implementation of common data structures, analysis methods, and utility functions relevant to wind plant OA.

deepsnap

Python library assists deep learning on graphs

wtphm

SCADA data pre-processing library for prognostics, health management and fault detection of wind turbines. Successor to https://github.com/lkev/wt-fdd

wt-fdd

Wind Turbine Fault Detection. Newer version @ https://github.com/lkev/wtphm

DeepTimeSeries

A Keras-based library for analysis of time series data using deep learning algorithms.

Multivariate-time-series-models-in-Keras

This repository contains a throughout explanation on how to create different deep learning models in Keras for multivariate (tabular) time series prediction.

hyperas

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Multivariate-Time-Series-forecast-using-seq2seq-in-TensorFlow

ludwig

Low-code framework for building custom LLMs, neural networks, and other AI models

datasets

TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

python-machine-learning-book-2nd-edition

The "Python Machine Learning (2nd edition)" book code repository and info resource

DeepMind-alphafold-repl

https://moalquraishi.wordpress.com/2018/12/09/alphafold-casp13-what-just-happened/

lstm_anomaly_thesis

Anomaly detection for temporal data using LSTMs

lstms_for_predictive_maintenance

LSTMS for Predictive Maintenance

Estimation-of-Remaining-Useful-Life-using-CNN

Convolutional Neural Network based regression approach for estimating machinery's remaining useful life

predict-remaining-useful-life

Predict remaining useful life of a component based on historical sensor observations using automated feature engineering

PySpark-Predictive-Maintenance

Predictive Maintenance using Pyspark

RUL-Net

Deep learning approach for estimation of Remaining Useful Life (RUL) of an engine