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This project is open-ended in that we are not looking for one right answer. As John Tukey stated, "The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data." We want you to ask interesting questions about data and give you a chance to explore.
This case study aims to identify patterns which indicate if a client has difficulty paying their installments which may be used for taking actions such as denying the loan, reducing the amount of loan, lending (to risky applicants) at a higher interest rate, etc. This will ensure that the consumers capable of repaying the loan are not rejected. …
Engage in the critical phase of Exploratory Data Analysis (EDA) using the tools and techniques from Python to uncover patterns, spot anomalies, test hypotheses, and identify the main structures of your dataset.
In this project, we have analyzed, explored and processed the data, developed and evaluated various classification and regression models to provide strategies for high returns with low risk for investors.
The goal of this project is to predict the future medical expenses of patients based on certain features. Factors affecting the medical expenses of the patients - age, gender, body mass index, region, smoking behavior, medical health expenses.
This is a combined framework which has all the EDA functions including bivariate and univariate analysis and classification models. EDA Functions can help to analyze the Data before running any ML model.
The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. They want to analyze the data to draw some actionable insights for the business. Suppose you are hired as a Data Scientist in this company and the Data Science team has shared some of the key questions.