Spark comparison: AWS vs. GCP
This post was written collectively by Michael Li and Ariel M’ndange-Pfupfu. The original post for this piece can be found at O’Reilly. There’s little doubt that cloud computing
This post was written collectively by Michael Li and Ariel M’ndange-Pfupfu. The original post for this piece can be found at O’Reilly. There’s little doubt that cloud computing
StatsModels & Scikit-learn are two popular packages for working with stats and machine learning in Python. Learn more about each from The Data Incubator.
SQLite and pandas are two common data manipulation tools, but SQLite selects and filters data faster while pandas joins and loads data faster.
Python can empower Excel to perform data manipulation and analysis much more efficiently.
Advanced tips for using conda – from installing Python packages to building your own packages in R.
Employees at risk of being replaced by automation need to transform themselves into data facilitators .
The 2016 Presidential Election was, in a single word, weird. So much happened… .
There is a library called threading in Python and it uses threads (rather than just processes) to implement parallelism .
We rank the top 20 of 110 JavaScript data visualization packages that are useful for Data Science .