Hello all, this is the 2nd part of our series, the series includes-

  1. Introduction and Exploratory Data Analysis
  2. Feature Engineering, Modelling and Deployment

In the previous blog, we saw detailed analysis of the data. Now, it’s time to start some feature engineering and building models.

Table of Content-

  1. Feature Engineering
  2. Modelling
  3. Deployment
  4. Future Work
  5. References

1. Baseline Model-

First, we will make prediction only based on medians of the data and we will use it as our baseline model.

Now, we will use median of data to make predictions, for each page we have taken median for each weekday and used it to make…


Table of Content-

  1. Real world objective/constraint
  2. Data source and overview
  3. Performance Metrics
  4. Existing Solution
  5. First cut Approach
  6. Exploratory Data Analysis
  7. Preprocessing and Feature Engineering
  8. Modelling
  9. Deployment
  10. Future Work
  11. Reference

Let’s get started

1. Problem Statement-

Hearing a species in a tropical rainforest is much more easier than seeing them and that is what we are going to do in this case study. We will be building model that can detect the species just by audio signals. If someone is in the forest, he might not be able to look around and see every type of bird and frog that are there but they can…


Hello readers, from the title you must have gotten the idea of what this blog is all about. We will be creating an end to end case study. This is my first time writing a blog, hope you all like it. I have divided this blog into a series of two blogs.

  1. Introduction and Exploratory Data Analysis
  2. Feature Engineering, Modelling and Deployment

Table of Content-

  1. Real world objective/constraint
  2. Data source and overview
  3. Performance Metrics
  4. Existing Solution
  5. First cut Approach
  6. Exploratory Data Analysis
  7. References

Let’s get started!

1. Problem statement-

This is a Kaggle competition problem which was held nearly 3 years ago. In this…

Tushar Aggarwal

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