DESCRIPTION: Here I am using ANN to predict outcomes in 2 models 1)churn rate in a bank (classification) 2)Total Power produced by combined cycle plant in full load(regression)
1)Churn rate in a bank (classification) This dataset talks about a bank’s churn rate. Churn is when people leave an organization
OBJECTIVE: The Objective here is to create a Geo demographic segmentation model to tell the bank which of the customers are at highest risk of leaving.
SOURCE-Kaggle
LIBRARIES USED: Pandas,Standard Scaler,Tensorflow(keras)--package,matplot
HIDDEN LAYERS- 2
EVALUATION: Confusion matrix,Accuracy
2)Total Power produced by combined cycle plant in full load(regression)
OBJECTIVE: The dataset contains 9568 data points collected from a Combined Cycle Power Plant over 6 years (2006-2011), when the power plant was set to work with full load. 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. A combined cycle power plant (CCPP) is composed of gas turbines (GT), steam turbines (ST) and heat recovery steam generators. In a CCPP, the electricity is generated by gas and steam turbines, which are combined in one cycle, and is transferred from one turbine to another. While the Vacuum is colected from and has effect on the Steam Turbine, he other three of the ambient variables effect the GT performance.
Attribute Information: Features consist of hourly average ambient variables
Temperature (T) in the range 1.81°C and 37.11°C, Ambient Pressure (AP) in the range 992.89-1033.30 milibar, Relative Humidity (RH) in the range 25.56% to 100.16% Exhaust Vacuum (V) in teh range 25.36-81.56 cm Hg Net hourly electrical energy output (EP) 420.26-495.76 MW The averages are taken from various sensors located around the plant that record the ambient variables every second. The variables are given without normalization.
Source-Kaggle
LIBRARIES USED: Pandas,Standard Scaler,Tensorflow(keras)--package,matplot
HIDDEN LAYERS- 2
EVALUATION: MSE,R2