Gradient checkpointing has emerged as a pivotal technique in deep learning, especially for managing memory constraints while maintaining high model performance. In the rapidly evolving field of AI, out-of-memory (OOM) errors have long been a bottleneck for many projects. Gradient checkpointing, particularly in PyTorch, offers an effective solution by optimizing ...

Interacting with Techtonique web app through Excel, using Visual Basic for Applications (VBA).

The video below provides several different examples and ways that data can be imported into Python.

Techtonique web app for data-driven decisions using Mathematics, Statistics, Machine Learning, and Data Visualization

In the realm of statistical analysis, critical values and p-values serve as essential tools for hypothesis testing and decision making. These concepts, rooted in the work of statisticians like Ronald Fisher and the Neyman-Pearson approach, play a crucial role in determining statistical significance. Understanding the distinction between critical values and ...

Markov Chain Monte Carlo (MCMC) is a class of algorithms used to sample from probability distributions when direct sampling is difficult or inefficient. It leverages Markov chains to explore the target distribution and Monte Carlo methods to per...

In Rhino 1.7.0, we began introducing the Rhino style guide and linting for box::use() calls to promote best practices for code quality. These linter functions were eventually separated from Rhino 1.8.0 into the {box.linters} package. Among the checks performed by {box.linters} are rules covering box::use() calls. For existing ...

It finally happened. It’s been almost two years since the first release of ChatGPT. It took the world by storm, to put it mildly. In the short period that followed, we now have multiple companies building Generative AI platforms that were unimaginable before late 2022. What a great time to ...