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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

data

deep-learning-for-uk-electricity-price-prediction

elektrik

energy_arbitrage_work_sample

kapsamli_derin_ogrenme_rehberi

Bu çalışma araştırmalar yaparken benzerlerine rastlayıp iyileştirerek derlemeye çalıştığım ve derin öğrenme (deep learning) konusunda kısa bir özet ve bolca kaynak yönlendirmesi olan (hatta sonunda koca bir liste var) hızlıca konuya giriş yapılabilinmesi için gereklilikleri özetlemektedir. Lütfen katkı vermekten çekinmeyin 👽

learning-pandas-second-edition

Learning pandas, Second Edition, published by Packt

lstm-autoencoder-for-anomaly-detection

AI deep learning neural network for anomaly detection using Python, Keras and TensorFlow

machine-learning-for-predictive-maintenance-on-wind-turbines

nasa-jet-engine-maintenance

ML Approaches for RUL Prediction, Anomaly Detection, Survival Analysis and Failure Classification

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

predictive_maintenance_w_lstm

Predictive_Maintenance_of_AircraftMotorHealth_with_LSTM_Method

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

tradingview-webhook

udemy_derinogrenmeyegiris

Udemy Derin Öğrenmeye Giriş Kursunun Uygulamaları ve Daha Fazlası

veri

wind_turbine_fault_detection

Import, clean, and prepare data and conduct machine learning for fault detection in a wind turbine

wind_turbine_scada_open_data

list of open data wind turbine data sets

wt_fault_identification

Wind Turbine Fault Identification using Machine Learning Techniques applied to SCADA data