Cyber attacks are becoming more common as more data are stored in digital form. Suspicious, and likely malicious, users are requesting access to unauthorized resources while hoping for vulnerable networks or systems. Continue reading to learn how to apply descriptive analytics to uncover who is generating these suspicious requests.
Neural networks are a growing area of research and are being applied to new problems every day. The classic examples are image classification, facial recognition, and self-driving cars. The future is uncertain, but there is a high probability that neural networks in some form will play a critical role in shaping it. Continue reading to learn about the core concepts and walk through an example in Python.
Data science is a broad and deepening field but one divisive question still remains. In this post, I compare and contrast Python and R for use in different data science tasks. Continue reading to learn which one emerges triumphant.
Shiny dashboards provide a simple and fast way to analyze and visualize data. Whether performing exploratory data analysis or building a robust tool for your client's executives, Shiny dashboards aid the data science process. Continue reading to walk through an example of constructing an R Shiny Dashboard.
