This article will be a theoretical and a short one. Code for every technique is easy to find on internet.

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Introduction

  1. Measurement error.
  2. Data corruption.
  3. True outlier(e.g. 72 runs in a single over of a cricket match.)


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Table of Contents

  1. Introduction.
  2. Problem Statement.
  3. Objectives.
  4. Exploratory Data Analysis(EDA).
  5. Indexing.
  6. Context Retrieval.
  7. Modelling.

Introduction

Problem Statement


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Table of Contents:

  1. Introduction.
  2. Problem statement and error metric.
  3. Objectives and data information.
  4. Exploratory Data Analysis(EDA).
  5. Feature Engineering.
  6. Modelling.

Introduction:

Keshav Rawat

Data Scientist. Sharing my knowledge using articles.

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