Making reproducible datasets possible

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MLOps has recently gained some limelight in Machine Learning community. With so many experiments, tracking, managing and orchestrating them with other components has been an important subject in discussion lately. In particular, datasets keep changing when you trying your experiments. You may be scaling, creating new features, eliminating features or…


Queries your data faster on GPU in seconds

SQL is an essential tool used heavily in the data world. Data Engineers, Data Scientists, Business Analysts use SQL for doing any fancy data querying and manipulations. Most industries are approaching that interesting juncture where the amount of data generated every day is unimaginable. The demand to process them efficiently…


Spaceship to speed your Python code!

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If you are reading this article or have stumbled upon it, I am sure you are tired of massive datasets with your computer freezing/crashing while creating new features and model building. You are on the hunt to find an approach that can help to make your life a little easier.


Machine Learning/DataScience Interview Series: How you should approach business case interviews to make it to the next stage

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This is my 3rd post in the “Machine Learning/Data Science Interview” series. The first post I wrote focused on technical interviews and can be found here. The second post I wrote focused on behavioral interviews and can be found here. In this post I am writing about case study interviews.


Machine Learning/DataScience Interview Series — Behavioral Interview

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This is my 2nd post in the “Machine Learning/Data Science Interview” series. The first post I wrote focused on Technical interviews which can be found here. In this article, I am sharing on Behavioral interviews. This is not a cookiecutter but purely a guide that might help navigate someone who…


Machine Learning/DataScience Interview Series — Technical Interview

I am writing this blog post series to share my journey what I learned when applying for Data Scientist/Machine Learning Engineer and interviewing positions at different companies. It was almost 5 years that I had applied for a job, and things have changed dramatically since I gave my last interview…


Why, How & When to use Sklearn’s Pipeline!

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If you are building a predictive model and achieving the desired accuracy without any preprocessing steps like cleaning the data, imputing missing values, you just happen to be the luckiest person in the world! But the most of today’s data do not speak up unless you perform a decent amount…


Make your Python code efficient!

The goal of writing this post is to put together all the tips/tricks I shared on my Twitter, in a single place during the month of July-2021. I try to learn new things in Python every day and share them via Twitter. …


Empower using command-line in Python!

Argparse is an in-built Python library that helps to build command-line interfaces over the Python code. Argparse means parsing the arguments. When I listened to Argparse for the first time I felt intimidated but once I started exploring and learning it became an integral part of my scripts. It provides…


Automate Time-Series problems!

Time series problems are one of the toughest problems to solve in data science. Traditional methods that are time-aware like ARIMA, SARIMA are great but lately they have largely been accompanied by the non-time aware and robust machine learning algorithms like XGBoost, LigthGBM, and so forth because of need and…

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