Reproducible and Shareable Notebooks Across a Data Science Team
At CybelAngel, we are a growing team of data scientists and a machine learning engineer, planning to double in size. Each of us contributes to projects and we use shareable notebooks before code industrialization for production. Notebooks: let’s focus on them. We talk specifically about Jupyter... Read more
How to Make Your Jupyter Notebook Standalone and Allow Others to Replicate Your Experiments
Editor’s note: Francesco is a speaker for ODSC West 2021. Be sure to check out his talk, “Reproducibility and Dependencies for Jupyter Notebooks,” there! Even though many developers (including data scientists) focus on their core problems when working on their experiments, one basic aspect can make... Read more
Data Science Notebooks | 2020 Review
2020 was a roller coaster, but the data science community is going strong. Interest in the data science domain has grown in the past year yet again. We dug into the data to learn more about the current state of a vital part of the data... Read more
Why You Should be Using Jupyter Notebooks
This article provides a high-level overview of Project Jupyter and the widely popular Jupyter notebook technology. The overarching message I’d like to convey is why you should be using Jupyter for your data science projects. I’ve been using it for all my Python machine learning work... Read more
Guide to R and Python in a Single Jupyter Notebook
Why pick one when you can use both at the same time? R is primarily used for statistical analysis, while Python provides a more general approach to data science. R and Python are object-oriented towards data science for programming language. Learning both is an ideal solution.... Read more
The Five Best Frameworks for Data Scientists
There are many tools that can help you when you start your data science career. Some of these tools you will be using them almost in every new project. In this post, we aim to highlight the five best frameworks for data scientists so that you... Read more