Pinned Repositories
3760creditrisk
For sharing project files related to 3760 - Credit Risk Assessment
beam
Apache Beam is a unified programming model for Batch and Streaming data processing.
Codes-in-R
Repository for R Programming on Coursera
Credit-Risk-Management
A binary classification model is developed to predict the probability of paying back a loan by an applicant. Customer previous loan journey was used to extract useful features using different strategies such as manual and automated feature engineering, and deep learning (CNN, RNN). Various machine learning algorithms such as Boosted algorithms (XGBoost, LightGBM, CatBoost) and Deep Neural Network are used to develop a binary classifier and their performances were compared.
NLP-for-8K-documents
Predicting returns from 8K documents using text analysis
Prediction-of-lithium-ion-batteries-SOH
Artificial Neural Network (ANN) has been used to estimate state-of-health (SOH) of lithium-ion batteriess. The batteries were stored at different storage temperature (35°C and 60°C) and conditions (fully-discharged and fully-charged) and their capacity was recorded for the duration of 10 months at one-month intervals.
SOC-estimation-of-lithium-ion-batteries
Various machine learning algorithms have been used to estimate state-of-charge (SOC) of calendar-aged lithium-ion pouch cells. Calendar life data was generated by applying galvanostatic charge/discharge cycle loads at different storage temperature (35°C and 60°C) and conditions (fully-discharged and fully-charged). The data was obtained at various C-rates for duration of 10 months at one-month intervals. The wininng model, Random Forest (RF), has achieved a R2 score of 99.98% and a mean absolute error (MAE) of 0.14% over test data, confirming the ability of RF to capture input-output dependency. The model will be employed to estimate the SOC of calendar-aged lithium-ion batteries which is essential for the reliable operation of electic vehicles (EVs).
udemy-spark-streaming
For Udemy students: the official repository of Rock the JVM's Spark Streaming course
winutils
winutils.exe hadoop.dll and hdfs.dll binaries for hadoop windows
3760creditrisk
For sharing project files related to 3760 - Credit Risk Assessment
ali-ghorbani-k's Repositories
ali-ghorbani-k/SOC-estimation-of-lithium-ion-batteries
Various machine learning algorithms have been used to estimate state-of-charge (SOC) of calendar-aged lithium-ion pouch cells. Calendar life data was generated by applying galvanostatic charge/discharge cycle loads at different storage temperature (35°C and 60°C) and conditions (fully-discharged and fully-charged). The data was obtained at various C-rates for duration of 10 months at one-month intervals. The wininng model, Random Forest (RF), has achieved a R2 score of 99.98% and a mean absolute error (MAE) of 0.14% over test data, confirming the ability of RF to capture input-output dependency. The model will be employed to estimate the SOC of calendar-aged lithium-ion batteries which is essential for the reliable operation of electic vehicles (EVs).
ali-ghorbani-k/Prediction-of-lithium-ion-batteries-SOH
Artificial Neural Network (ANN) has been used to estimate state-of-health (SOH) of lithium-ion batteriess. The batteries were stored at different storage temperature (35°C and 60°C) and conditions (fully-discharged and fully-charged) and their capacity was recorded for the duration of 10 months at one-month intervals.
ali-ghorbani-k/Credit-Risk-Management
A binary classification model is developed to predict the probability of paying back a loan by an applicant. Customer previous loan journey was used to extract useful features using different strategies such as manual and automated feature engineering, and deep learning (CNN, RNN). Various machine learning algorithms such as Boosted algorithms (XGBoost, LightGBM, CatBoost) and Deep Neural Network are used to develop a binary classifier and their performances were compared.
ali-ghorbani-k/3760creditrisk
For sharing project files related to 3760 - Credit Risk Assessment
ali-ghorbani-k/beam
Apache Beam is a unified programming model for Batch and Streaming data processing.
ali-ghorbani-k/Codes-in-R
Repository for R Programming on Coursera
ali-ghorbani-k/NLP-for-8K-documents
Predicting returns from 8K documents using text analysis
ali-ghorbani-k/udemy-spark-streaming
For Udemy students: the official repository of Rock the JVM's Spark Streaming course
ali-ghorbani-k/winutils
winutils.exe hadoop.dll and hdfs.dll binaries for hadoop windows