Python pip Tips for Data Scientists
Data Scientists use to work with Anaconda Environments and for installing packages they use to run the “conda” commands. However,
Unix Sed Command Tutorial with Examples
Sed (stream editor) is a very powerful tool for parsing and transforming text that was developed back in 1973 at
How to connect Snowflake with S3 and EC2 using Python
We have provided you with several tutorials in Snowflake. In this example, we consider the scenario where we have to
AWK Tutorial for Data Scientists and Engineers
AWK appeared back in 1977 and is a programming language designed for text processing that is used mainly for data
A Complete Guide of How to Choose and Apply the Right Statistical Test in Python
We often underestimate statistics and their importance and from my own experience, I can tell for certain that it’s the
Interview Question: A Variation of Russian Roulette
For Data Science positions, it is common to be asked questions about probabilities. One example is the following: The Question
How to Generate the Requirements of your Python project based on your Imports
We have provided many tutorials on how to generate the requirements.txt for your python project without environments, how to work
How to Schedule Tasks in Snowflake
We have started a series of Snowflake tutorials, like How to Get Data from Snowflake using Python, How to Load
Data Validation for Machine Learning using TFDV
After the Machine Learning model deployment we need somehow to validate the incoming datasets before we move on and input
How to Sync your Working Environment with Docker Jupyter Notebooks
Data Scientists love to work with Jupyter notebooks. It is possible that in the machine that you have to work
How to work with VS Code and Virtual Environments in Python
We have provided examples of how to work with conda environments. In this post, we will provide you a walk-through
