提交 83f92be6 编写于 作者: P Pavol Mulinka

added roadmap link

上级 2967a4e0
Pytorch-widedeep is being developed and used by many active community members. Your help is very valuable to make it better for everyone. Pytorch-widedeep is being developed and used by many active community members. Your help is very valuable to make it better for everyone.
- Check for the [Roadmap](https://github.com/jrzaurin/pytorch-widedeep/projects/1) or [Open an issue](https://github.com/jrzaurin/pytorch-widedeep/issues) to report problems or recommend new features and submit a draft pull requests, which will be changed to pull request after intial review - Check for the [Roadmap](https://github.com/users/jrzaurin/projects/3) or [Open an issue](https://github.com/jrzaurin/pytorch-widedeep/issues) to report problems or recommend new features and submit a draft pull requests, which will be changed to pull request after intial review
- Contribute to the [tests](https://github.com/jrzaurin/pytorch-widedeep/tree/master/tests) to make it more reliable. - Contribute to the [tests](https://github.com/jrzaurin/pytorch-widedeep/tree/master/tests) to make it more reliable.
- Contribute to the [documentation](https://github.com/jrzaurin/pytorch-widedeep/tree/master/docs) to make it clearer for everyone. - Contribute to the [documentation](https://github.com/jrzaurin/pytorch-widedeep/tree/master/docs) to make it clearer for everyone.
- Contribute to the [examples](https://github.com/jrzaurin/pytorch-widedeep/tree/master/examples) to share your experience with other users. - Contribute to the [examples](https://github.com/jrzaurin/pytorch-widedeep/tree/master/examples) to share your experience with other users.
......
Pytorch-widedeep is being developed and used by many active community members. Your help is very valuable to make it better for everyone. Pytorch-widedeep is being developed and used by many active community members. Your help is very valuable to make it better for everyone.
- Check for the [Roadmap](https://github.com/jrzaurin/pytorch-widedeep/projects/1) or [Open an issue](https://github.com/jrzaurin/pytorch-widedeep/issues) to report problems or recommend new features and submit a draft pull requests, which will be changed to pull request after intial review - Check for the [Roadmap](https://github.com/users/jrzaurin/projects/3) or [Open an issue](https://github.com/jrzaurin/pytorch-widedeep/issues) to report problems or recommend new features and submit a draft pull requests, which will be changed to pull request after intial review
- Contribute to the [tests](https://github.com/jrzaurin/pytorch-widedeep/tree/master/tests) to make it more reliable. - Contribute to the [tests](https://github.com/jrzaurin/pytorch-widedeep/tree/master/tests) to make it more reliable.
- Contribute to the [documentation](https://github.com/jrzaurin/pytorch-widedeep/tree/master/docs) to make it clearer for everyone. - Contribute to the [documentation](https://github.com/jrzaurin/pytorch-widedeep/tree/master/docs) to make it clearer for everyone.
- Contribute to the [examples](https://github.com/jrzaurin/pytorch-widedeep/tree/master/examples) to share your experience with other users. - Contribute to the [examples](https://github.com/jrzaurin/pytorch-widedeep/tree/master/examples) to share your experience with other users.
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...@@ -29,9 +29,9 @@ Pytorch ...@@ -29,9 +29,9 @@ Pytorch
The content of this document is organized as follows: The content of this document is organized as follows:
- [pytorch-widedeep](#pytorch-widedeep) - [**pytorch-widedeep**](#pytorch-widedeep)
- [Introduction](#introduction) - [Introduction](#introduction)
- [The deeptabular component](#the-deeptabular-component) - [The ``deeptabular`` component](#the-deeptabular-component)
- [Acknowledgments](#acknowledgments) - [Acknowledgments](#acknowledgments)
### Introduction ### Introduction
...@@ -75,9 +75,10 @@ $$ ...@@ -75,9 +75,10 @@ $$
Where $W$ are the weight matrices applied to the wide model and to the final Where σ is the sigmoid function, *'W'* are the weight matrices applied to the wide model and to the final
activations of the deep models, $a$ are these final activations, and activations of the deep models, *'a'* are these final activations,
$\phi(x)$ are the cross product transformations of the original features $x$. φ(x) are the cross product transformations of the original features *'x'*, and
, and *'b'* is the bias term.
In case you are wondering what are *"cross product transformations"*, here is In case you are wondering what are *"cross product transformations"*, here is
a quote taken directly from the paper: *"For binary features, a cross-product a quote taken directly from the paper: *"For binary features, a cross-product
transformation (e.g., “AND(gender=female, language=en)”) is 1 if and only if transformation (e.g., “AND(gender=female, language=en)”) is 1 if and only if
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