Gunnika Batra Google Code-in Mentor @Tensorflow | Lead @WTMBVP | GitHub Campus Expert | Former Data Analytics Intern @SHEROES | Python and food enthusiast

Data Science Bootcamp – Day #15 – Distribution, Skewness and Data Cleaning

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Hello learners!

Let’s broaden our statistics knowledge and learn about Distribution and Skewness today. There are a number of distributions in statistics but we’ll focus on Normal Distribution as most statistical models rely on it.

Data skewness is one of the important challenges that data scientists often face in real time case studies. We’ll figure out what positive and negative skewness means in statistics.

We have a well-documented notebook for performing Exploratory Data Analysis on Wine Dataset. You’ll figure out which of the two wines- Red or White have a better quality through the means of various beautiful graphs.

Apart from these, we have a great blog emphasizing all the steps of Data Cleaning using the Russian Housing Dataset. It covers everything we’ve learnt till now. You’ll analyse and visualise data, detect outliers, remove irrelevant and inconsistent values and get structured, clean data at the end.

Find the module below:

Happy learning!
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