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Understanding the problem statement

Importing the train and test dataset

Installing packages from R and GoogleMaps in R

Initializing important libraries and understanding its functions

Calculating distances in R using latitude and longitudinal points

Plotting scatter plots between different variables

Performing basic EDA and checking for null values

Imputing null values

Learning different techniques for imputing categorical and numeric variables

Changing character to factor vector in R

Removing unnecessary variables

Time stamping

Binning and visualizing time stamped data

Make a new dataset through data table

Selecting the model for training the pre-processed Dataset

Defining parameters for the model

Defining evaluation metrics for evaluating the model

Applying Random Forest model

Making the final predictions and saving it in CSV format

This data science in python project predicts if a loan should be given to an applicant or not. We predict if the customer is eligible for loan based on several factors like credit score and past history.

The goal of this data science project is to build a predictive model and find out the sales of each product at a given Big Mart store.

Deep Learning Project- Learn to apply deep learning paradigm to forecast univariate time series data.

19-Dec-2015

03h 21m