How to detect and treat outliers

Read Time: 6 min In this article, we are going to understand in-depth and detail about outlier-Statistical and Programming approaches, how to detect and treat outliers so that they won’t screw up the model performance. So read this article till the end, you will get to know how important outliers are while data-preprocessing. Table of content Why study outlier? … Read more

Frequently Asked Interview Questions on Data Analysis

Read Time: 4 min This post mainly focuses on interview questions asked in the data science interview. The primary purpose of this post is to help you to understand and learn concepts through questions. So let’s prepare together! 1. Why normalization is needed? Is it always necessary to normalize the data? Answer: Normalization brings all features in the same … Read more

Data Analysis (Part-3): Feature Engineering

Read Time: 6 min So, Here we are on part-3 of Data Analysis: Feature Engineering At first we need to understand, what does it mean by feature engineering? Feature Engineering is a part of data analysis where using domain knowledge of data, features are transformed or generated or extracted to improve the model performance. Let’s dive in deeper! Feature … Read more

Data Analysis (Part-2): Data Visualization

Read Time: 6 min Through data wrangling, we have seen basic pre-processing methods to make the data in usable form. So just think, what should be our next step..? Exploratory Data Analysis In simple terms, every process which gives insights about data. Now questions is, do I really need that? Exploratory data analysis is mandatory as it helps to … Read more

Data Analysis (Part-I): Data Wrangling

Read Time: 5 min Let’s take first step towards journey of learning.. For any manipulation, we need to understand the data first. Basically, data is of two types: Unstructured: A form of data, where data points are not in particular order and it’s not possible to extract information from that directly such as raw text data, image data (where … Read more

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