RStudio AI

Optimizers in torch

Today, we wrap up our mini-series on torch basics, adding to our toolset two abstractions: loss functions and optimizers.

Feb 11, 2025 - 09:55
 0
Optimizers in torch
Today, we wrap up our mini-series on torch basics, adding to our toolset two abstractions: loss functions and optimizers.
Read More

Tags:

Previous Article

sparklyr.flint 0.2: ASOF Joins, OLS Regression, and additional summarizers

Next Article

Using torch modules

Related Posts

sparklyr 1.7: New data sources and spark_apply() capabilities, better interfaces for sparklyr extensions, and more!

sparklyr 1.7: New data sources and spark_apply() capabi...

Feb 11, 2025  0

sparklyr 1.6: weighted quantile summaries, power iteration clustering, spark_write_rds(), and more

sparklyr 1.6: weighted quantile summaries, power iterat...

Feb 11, 2025  0

Hierarchical partial pooling, continued: Varying slopes models with TensorFlow Probability

Hierarchical partial pooling, continued: Varying slopes...

Feb 11, 2025  0