Use the vitals package with ellmer to evaluate and compare the accuracy of LLMs, including writing evals to test local models.

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Learn how to calculate the area under curves numerically using Python in this step-by-step tutorial! This video covers essential numerical integration techniques, including the trapezoidal and Simpson ...

Abstract: New statistical models must exist for big data analysis in technology because they need to work with datasets of many dimensions to uncover valuable insights. The Generalized Linear Model ...

Introduction The importance of conducting qualitative research alongside clinical trials of complex healthcare interventions is well established. There are various ways in which these two ...

pandas is the premier library for data analysis in Python. Here are some advanced things I like to do with pandas DataFrames to take my analysis to the next level. Change the index of a DataFrame On a ...

In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Single-cell technologies have revolutionized our ability to interrogate biological systems at unprecedented resolution, revealing complex cellular heterogeneity and dynamic processes that underlie ...

Benchtop GC–MS combines gas chromatography's separation power with mass spectrometry's detection capabilities, offering universal and selective analysis in one system. The three GC–MS analysis ...

If you’re new to Python, one of the first things you’ll encounter is variables and data types. Understanding how Python handles data is essential for writing clean, efficient, and bug-free programs.