Data Regress.

A data science blog documenting learning, projects, concepts, and how-tos of this incredible field.

Tag: regression

Apartment Pricing: Model Development, Training, and Predictions

September 27, 2020 / / 2 Comments

Welcome to the final part of the project series “Apartment Pricing: Advanced Regression Techniques.” 

I highly recommend visiting previous posts in this series:

You can find all the working shown in this series at my GitHub repository here.

Introduction

So, this is all we’ve been building up to, Predicting prices. 

To reach this stage, we covered the following stages of a data science project lifecycle:

  1. Business Understanding
  2. Data Acquisition
  3. Data Preparation
  4. Data Visualization & Exploratory Analysis

In the final part of the series, we will see how we can:

  1. Final tuning of our dataset
  2. Divide our dataset into training and testing samples
  3. Training our machine learning models
  4. Testing those models
  5. Output our results
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Apartment Pricing: Advance Regression Techniques

September 22, 2020 / / 0 Comments
Dubai real estate
Credit: Kate Trysh

Introduction

This project is inspired by a famous Kaggle competition called House Prices: Advanced Regression Techniques.  The original project on Kaggle is based on the Boston Housing dataset and is an ideal project for newbies to hone their skills on.

The original project on Kaggle gives you full opportunity to practice data cleaning, exploratory analysis, and modeling. However, one aspect of the data science project lifecycle was missing, i.e., data scavenging and extraction. The data is already extracted for you, and you don’t know how the information was gathered.

My objective was to achieve the same goals of the original project, but by doing so, using my dataset. Instead of Boston housing, I started looking into the Dubai real estate market and opted to use one of the prominent real estate property portals for my data extraction.

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How I started my journey towards Data Science

August 12, 2020 / / 0 Comments

So, here goes nothing.

Since the beginning of March, I’ve been working my full-time job from home (WFH) due to all this COVID-19. These WFH circumstances consequently give you an ample amount of time, in comparison to when you are at your workplace. Now that I had some spare time, I used it to reflect on my career.

While thinking about my career, I’ve always been fascinated with the field of Data Science but was always discouraged by thinking that it is only for people who are seasoned statisticians, or mathematicians, as the roots of data science go deep in these two fields. And trust me, I’m neither. But still, I wanted to give it a shot.

During this WFH period, my employer-sponsored our learning through coursera.com, which is a blessing in disguise. Now the only thing left is a will to talk the first step. I started scouting for programs on Coursera and also started researching what I needed to get started.

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