Raja Narasimhan

Data Scientist 2 at Mastercard Pune

Predicting Output Power

less than 1 minute read

Predicting output Power (Done during tenure as Intern in Adani, Ahmedabad)

Here I got the dataset from UCI. Features consist of hourly average ambient variables Temperature (T), Ambient Pressure (AP), Relative Humidity (RH) and Exhaust Vacuum (V) to predict the net hourly electrical energy output (EP) of the plant. I used 50 fold Cross Validation with XGB and my RMSE was around 4 for the whole dataset

https://github.com/rajanarasimhan/Power_ML

Twitter Facebook LinkedIn

You May Also Enjoy

Web App For Alzheimer Detection

less than 1 minute read

Created Web-App for Alzheimer Detection

Image Based Android Malware Detection Models Using Static And Dynamic Features

1 minute read

Image-based Android Malware Detection Models using Static and Dynamic Features

Analysis Of Computer Vision Techniques In Malware Classification

less than 1 minute read

Analysis of Computer Vision Techniques in Malware Classification

Blood Cells Classification

less than 1 minute read

Here I have used a dataset which has four categories of blood cells EOSINOPHIL, LYMPHOCYTE, MONOCYTE and NEUTROPHIL.