20 Data Science articles from February 2023

Five statistical paradoxes that data scientists should be aware of in order to do accurate analysis

What Pentagon leaders say they have learned from a year of battle in Ukraine:"The power of information is winning”

Software to sow doubts as you meta-analyze  

Machine learning is vulnerable to a wide variety of attacks. How the adversary can disrupt model training and even introduce backdoors

How Pandas alternatives—Polars, DuckDB, Vaex, and Modin—stack up to one of the most popular libraries in Python

Six of the most important types of machine learning algorithm 

“Big Data is real, but most people may not need to worry about it”

The ChatGPT prompts any data scientist must use

No, chatbots aren’t sentient. Here’s how their underlying technology works

5 Common Data Analytics Types Explained in Laymen’s Terms

Using the metaverse to virtually assemble and test AI war machines for the US military

Researchers discover a more flexible approach to machine learning—liquid neural nets

The evolving role of the data engineer

Top Predictive Analytics Trends in 2023

Even the pentagon Is using ChatGPT—the DoD’s used it to write a press release about a new counter-drone task force

How NGA Is integrating commercial analytic services into agency workflows

Python string matching without complex RegEx Syntax

Six python libraries especially useful to data engineers and natural language processing

Can ChatGPT write better code than Data Scientist? 

Researchers say ChatGPT can “weed out errors with sample code and fix it better than existing programs designed to do the same.”