In one of my previous posts "The General Problem Solver," I discuss the debate over whether a physical symbol system is necessary and sufficient for intelligence. The developers of one of the early AI programs were convinced it did, but philosopher John Searle presented his Chinese room argument as a rebuttal to this theory. Searle concluded that […]
Data science teams do more than just analytics and reports. They need to discover insights about your data.
The key ingredient for a successful data scientist is a curious, skeptical, and innovative mind. However, data scientists also need to be familiar with the tools of the trade, various technologies, which can be broken down into the following categories: Moving Beyond the Tools Keep in mind that tools are just that — devices for […]
Machine learning algorithms see patterns in the data without being explicitly programmed. ML is a subset of artificial intelligence and also uses concepts from data science.
Supervised and unsupervised machine learning are two different techniques that you discover insights from your data.
To be a successful data science team, a data scientist needs to collaborate with every other team member. These team structures will foster good communication for every data-driven product or project coming down the pipeline.
