Have you read about the MICE...

A advanced technique for more precise and accurate missing data imputation without worrying much about anything...

Not yet???

Read it here...

"Multi-variate Imputation of Chained Equation" https://quickdatascienceds.blogspot.com/2021/09/multi-variate-imputation-of-chained.html?m=1

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Hello friends...

Let's see a unique way to Exploratory Data Analysis EDA, using a python Library...

This library eases and reduce our work to just few lines of codes.

"Pandas Profiling -- A Unique way to Data Analysis" https://quickdatascienceds.blogspot.com/2021/07/pandas-profiling-unique-way-to-data.html?m=1

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Hello friends...

Today we will be discussing about something that we already know.. but tend to ignore it and its impact on larger scale...

"Outliers" https://quickdatascienceds.blogspot.com/2021/09/outliers.html?m=1

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Technique used in feature engineering....

With a simple method from feature engine library to achieve imputation...

Imputation techniques:- https://quickdatascienceds.blogspot.com/2021/08/imputation-techniques.html?m=1


"Imputation Using Feature Engine" https://quickdatascienceds.blogspot.com/2021/09/imputation-using-feature-engine.html?m=1

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Hello friends...

A very talked topic when we talk about Hive is type of tables.
This is also an important interview questions and acts as a decider for your further interview direction.

So let's see what are the different types of tables in hive and the difference between them..

https://quickdatascienceds.blogspot.com/2021/10/internal-vs-external.html

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Hello friends...

We read about the outliers in our previous posts... But what about handling them.!!!

So, we would like to present you a technique popularly known as "capping/censoring/winsorizing" .

"Outliers Capping" https://quickdatascienceds.blogspot.com/2021/10/outliers-capping.html?m=1

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Hii...

We studied about Partitioning in Hive... But have we ever thought what would happen if the Partitioning column is NULL.?

No..!!

Don't worry.... We have got you an article on how to handle NULL values in partitioning column.

"Hive Default Partition" https://quickdatascienceds.blogspot.com/2021/10/hive-default-partition.html?m=1

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Hello friends...

Time to learn "A Sweat way to Exploratory Data Analysis --- Sweetviz" https://quickdatascienceds.blogspot.com/2021/07/a-sweat-way-to-exploratory-data.html?m=1

Exploratory Data Analysis is the most important and necessary step that we need perform in our ML journey...

What better way than achieving this in a single line of code through sweetviz.

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Hello friends...

Another python library that we can use for performing the exploratory Data Analysis is t

"The Explorer of Data Sets -- Dora" https://quickdatascienceds.blogspot.com/2021/08/the-explorer-of-data-sets-dora.html?m=1

A Quick and easy library for EDA and basic data pre processing..

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Hello friends...

Do you know..!!! SQL has some powerful commands that changes the way of what we actually think of SQL.

These commands are known Windows Functions.

"Windows Functions in SQL" https://quickdatascienceds.blogspot.com/2021/10/windows-functions-in-sql.html?m=1

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Hello friends...

We are often mislead in our analysis by introduction of few outliers, their presence can change the entire analysis... One easy to deal with them is..

"Trimming the Outliers" https://quickdatascienceds.blogspot.com/2021/09/trimming-outliers.html?m=1

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Hiiiii.....

We may use more and more powerful hard drives, RAMs, GPU, CPU.. etc etc. But we might still not get a fast performance when we start working with Big Data... This is due to the improper db and table structure.

To achieve a better performance we need to properly index our tables.

So let's learn about "Indexes in SQL" https://quickdatascienceds.blogspot.com/2021/10/indexes-in-sql.html?m=1


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Hello friends...

We are pleased to announce that we are launching a new series "Quick Reads" covering some of very important topics in very compact and easy-to-remember manner.

So bringing the first topic in this QUICK READS:-

"Encoding" -- way to convert non numerical variables into numerical variables.
https://quickdatascienceds.blogspot.com/2021/10/encoding.html?m=1

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Hello DS enthusiasts...

Bringing to you another important Quick Read -- Count Frequency Encoding.

A technique used in categorical variable encoding...

"Count Frequency Encoding" https://quickdatascienceds.blogspot.com/2021/10/count-frequency-encoding.html?m=1

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Hello friends....

Another technique that is most commonly used in categorical variables encoding is...

"Mean Encoding or Target Encoding" https://quickdatascienceds.blogspot.com/2021/10/mean-encoding-or-target-encoding.html?m=1

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https://t.me/quickdatascience

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Hello...

One hot encoding... We all have heard this name many times...

Let's have a look at what it is.. and how to work with it.

"One Hot Encoding" https://quickdatascienceds.blogspot.com/2021/10/one-hot-encoding.html?m=1

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Hello friends...

Another topic in our series of Quick Reads - Encoding.

"Ordinal Encoding" https://quickdatascienceds.blogspot.com/2021/10/ordinal-encoding.html?m=1

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Hello...

What to do in case you have too many values in a variable..!!!

Let's see a technique we can use to encode such variables..

"Rare Label Encoding" https://quickdatascienceds.blogspot.com/2021/10/rare-label-encoding.html?m=1

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Hello friends...

Still not clear to how to encode your variables..!!!

Let system decide...

"Decision Tree Encoding" https://quickdatascienceds.blogspot.com/2021/10/decision-tree-encoding.html?m=1

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Wishing you all a very happy dhanteras... 😊