The #1 Mistake Companies Make When Creating Their Data Science Foundation
85 % of data science projects fail because companies are obsessed with complex models such as deep learning. Simple models often can solve their problems.
85 % of data science projects fail because companies are obsessed with complex models such as deep learning. Simple models often can solve their problems.
Here are the six data quality dimensions and how to use continuous data quality assessments in your business.
Maintain clean Python code by automatically running flake8 and isort before you commit changes to git.
Deep learning has several advantages over other machine learning methods. But not always.
Here are the best practices for a manageable, scalable, and easily understandable python project structure.
Python is the perfect programming language for a beginner. Here’s a curated list of free resources to guide the learning process.
Venv is good. But managing them and the dependencies is a hustle. Poetry can create environments and help you package and publish your app.
Skimpy makes it incredibly easy to summarize datasets in notebooks and terminals.
Plotly dash apps are the fastest way to build production-grade dashboards in python.
Everything we need to start data science is affordable and accessible