hidayetyakupoglu's repositories
Wind_Turbine_SCADA_open_data
list of open data wind turbine data sets
NASA-Jet-Engine-Maintenance
ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification
Anomaly-Detection
UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.
Applications-of-AI-for-Predictive-Maintenance
Nvidia DLI workshop on AI-based predictive maintenance techniques to identify anomalies and failures in time-series data, estimate the remaining useful life of the corresponding parts, and map anomalies to failure conditions.
Applied-AI-Study-Group
This is the repository for the content of inzva Applied AI Study Group.
auto-py-to-exe
Converts .py to .exe using a simple graphical interface
binance-connector-python
a simple connector to Binance Public API
Learning-Pandas-Second-Edition
Learning pandas, Second Edition, published by Packt
hisse
BIST 100
LSTM-Autoencoder-for-Anomaly-Detection
AI deep learning neural network for anomaly detection using Python, Keras and TensorFlow
pandapower
Convenient Power System Modelling and Analysis based on PYPOWER and pandas
pandas-ta
Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators
Predictive-maintenance-cost-minimization-using-ML-ReneWind
The aim to decrease the maintenance cost of generators used in wind energy production machinery. This is achieved by building various classification models, accounting for class imbalance, and tuning on a user defined cost metric (function of true positives, false positives and false negatives predicted) & productionising the model using pipelines.
predictive-maintenance_onemli
Demonstration of MapR for Industrial IoT
pump-it-up
DrivenData challenge for fun. Using LightGBM + streamlit for interactive reporting
ReneWind-Predictive-Maintenance
“ReneWind” is a company working on improving the machinery/processes involved in the production of wind energy using machine learning and has collected data of generator failure of wind turbines using sensors. They have shared a ciphered version of the data, as the data collected through sensors is confidential (the type of data collected varies wi
Software-Development-for-Algorithmic-Problems_Project-3
Time Series Forecasting using RNN, Anomaly Detection using LSTM Auto-Encoder and Compression using Convolutional Auto-Encoder
streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io
switchboard-dapp
Energy Web Switchboard UI
Udemy_DerinOgrenmeyeGiris
Udemy Derin Öğrenmeye Giriş Kursunun Uygulamaları ve Daha Fazlası
WT_fault_identification
Wind Turbine Fault Identification using Machine Learning Techniques applied to SCADA data