An end to end solution to the hospital readmission problem. This blog will mainly cover the exploratory data analysis, data preprocessing part , Model training, Model Comparison and Demo of the final app.

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Table of content:

* Problem Explanation

* Understanding the Data

* Existing Approaches

* Exploratory Data Analysis

* First Cut Approach

* Data Preprocessing

* Bivariate Analysis

* Encoding Features

* Model Training

* Model Comparison

* App Demo Video

* Future Work

* References

Problem Explanation

When a patient who is suffering from Hyperglycemia is admitted to a hospital, he is supposed to be taken good and systematic care. Mismanagement of…

A detailed case study of customer complaints in a firm and training multiple machine learning models.

Table of contents:

  • Problem Introduction
  • Exploratory Data Analysis
  • Feature Engineering
  • ML Models (SVM, GaussianNB, Decision Tree, XGBoost)
  • Summary of ML Models

Problem Introduction

As a firm or any service providing company, we receive multiple complaints from customers. Receiving complaints is nothing but another way of improving our services towards the customer. In customer handling, it is of utmost importance to work towards customer satisfaction and cannot be achieved untill and unless we address the complaints of our customer sincerely and efficiently. If we fail to solve…

A walk through the concept of proportional sampling by an example explanation with python codes to perform the same.

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Table of contents:

  • What is proportional sampling?
  • Example problem
  • Algorithm
  • Python Code
  • Summary

What is proportional sampling?

In most simple words, proportional sampling is a sampling of a population in which the probability of finding an element is proportional to some common shared attribute or property of all the elements in the population. For example, suppose you have a set of numbers, say {2,5,8,15,46,90}, and you want to randomly pick a number but you don’t want the probability to be uniform. …

Table of contents:

  • Why evaluation is necessary?
  • Confusion Matrix
  • Accuracy
  • Precision & Recall
  • Log Loss
  • Coefficient of Determination (R-Squared)
  • Summary

Why evaluation is necessary?

Let me start with a very simple example.

Robin and Sam both started preparing for an entrance exam for engineering college. They both shared a room and put equal amount of hard work while solving numerical problems. They both studied almost the same hours for the entire year and appeared in the final exam. Surprisingly, Robin cleared but Sam did not. When asked, we got to know that their was one difference in their strategy of preparation, “test series”…

Random Variables follow different types of distribution in probability space which decides their behaviour and helps in predictions.

Table of contents:

  • Introduction
  • Gaussian/Normal Distribution
  • Binomial Distribution
  • Bernoulli Distribution
  • Log Normal Distribution
  • Power Law Distribution
  • Uses of Distributions


Whenever we come across any experiment in probability, we talk about random variable which is nothing but the variable which takes the expected outcomes of that experiment. For example, when we roll a dice, we expect a value from the set {1,2,3,4,5,6}. So we define a random variable X which takes these values every time we roll.

Depending upon the experiment, the random…

Saurabh Raj

IIT Jammu’20

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