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.

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

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

Let’s get started

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

Let’s get started!

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

Tushar Aggarwal

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