Exploratory data analysis and preprocessing, cloud computing models, big data and distributed systems, and data integration and visualisation.
No model, however sophisticated, fixes bad input data — the practical groundwork covered here is usually where a data science project actually spends most of its time, well before any model gets trained 1 . The term…
"The cloud" is not one thing — it's a spectrum of how much of the infrastructure stack a provider manages versus how much is left to the customer, and knowing where a given service sits on that spectrum is the…
A dataset that fits comfortably on one machine can be processed the ordinary way — load it, compute, done. Past a certain scale, that stops being an option: the data doesn't fit in one machine's memory, or one machine's…
Useful analysis rarely starts from one clean table — it starts from several messy, differently-structured sources that have to be combined before any question can be asked of them, and ends with a result that has to be…