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The German credit dataset contains information on 1000 loan applicants. Each applicant is described by a set of 20 different attributes. Of these 20 attributes, seventeen attributes are discrete while three are continuous. The main idea is to use techniques from the field of information theory to select a set of important attributes that can be used to classify tuples. In this data science project, you will train a neural network using these attributes; the neural network is then used to classify tuples.
Given a partial trajectory of a taxi, you will be asked to predict its final destination using the taxi trajectory dataset.
In this neural network project, we are going to develop an algorithm that will automatically identify the boundaries of the car images which will help to remove the photo studio background.
Machine Learning Project in R -Predict which customers will leave an insurance company in the next 12 months.