Deep Function Learning Examples
Before You Begin
This tab presents example code for using the RPN model to tackle various
deep function learning tasks with the tinybig library.
We assume you have already read the PRN paper and completed the provided tutorials, so we won't repeat technical information about model components. Instead, we'll provide runnable code and model configurations that directly address these deep function learning problems.
Example Organization
The examples are organized according to the data modalities into different sections.
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Examples of Continuous Functions
Examples to use
tinybiglibrary for continuous function approximation.
Examples include
- Elementary function approximation
- Composite function approximation
- Feynman function approximation
- etc.
-
Examples of Vision Processing
Examples to use
tinybiglibrary for vision data processing.
Examples include
- MNIST hand-written digit classification
- CIFAR10 image object recognition
- etc.
-
Examples of Language Processing
Examples to use
tinybiglibrary for language data processing.
Examples include
- IMDB review polarity classification
- AGNews news topic inference
- SST2 text sentiment prediction
- etc.
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Examples of Tabular Processing
Examples to use
tinybiglibrary for tabular data processing.
Examples include
- Iris species prediction
- Diabetes disease diagnosis
- Banknote authentication inference
- etc.