Databases are the houses of our data and data scientists HAVE TO HAVE A KEY! In this article, I discuss some lesser known concepts of SQL that data scientists do not familiarize themselves with.

A collection of cheat sheets that will help you prepare for a technical interview, assessment tests, class presentation, and help you revise core data science concepts.

In this article, I will show you how to create a web scraper from scratch in Python.

Transform your machine learning models into a web app and share them with your friends and colleagues.

Read this guide through the most common data science programming languages and when to use them in data science.

Logistic regression is an extension of linear regression to solve classification problems. Read more on the specifics of this algorithm here.

This tutorial provides only a brief synopsis of the data warehouse in Snowflake, which we will go through in more detail.

Transformer based language models such as BERT are really good at understanding the semantic context because they were designed specifically for that purpose. BERT outperforms all NLP baselines, but as we say in the scientific community, “no free lunch”. How can we use BERT to classify long text documents?

Are you trying to teach yourself machine learning from scratch, but aren’t sure where to start? I will attempt to condense all the resources I’ve used over the years into 7 steps that you can follow to teach yourself machine learning.