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 […]
How to deal with missing data in data science and possible solutions to avoid coming to the wrong conclusions.
Neural network gradient descent uses a different type of machine learning algorithm to help with the backpropagation of massive datasets.
Choosing the right machine learning algorithm is one of the greatest challenges facing your data science team.
When you start your neural network you want to assign random neural network weights to each node in the network.
The key difference between a data warehouse and a data lake is how the database is structured and how it's used.
