Lending Club Database Analysis and Machine Learning Alghoritms

This project took the following steps:

• Starter Code (importing libraries, setting up the description and main dataframes and seeing whether there are missing values)
• Exploratory Data Analysis (understanding the importance of each column and their correlations before transforming the data)
• Data Pre Processing (transforming the data - filling in, removing, creating dummy variables and transforming the format of the data to prepare for the model)
• Train/Test Split (after having the data ready, we can split the data into training and testing data and normalize it with a MinMaxScaler)
• Creating the model (a model with 4 layers, implemented dropout of 20% and early stopping, using the adam optimizer)
• Evaluating the model and testing with a new random client (checking for overfitting, and evaluating the model with a classification report and a confusion matrix)