{"repo":"jrzaurin/pytorch-widedeep","free":true,"listed":false,"github":"https://github.com/jrzaurin/pytorch-widedeep","clone":"git clone https://github.com/jrzaurin/pytorch-widedeep.git","description":"A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch","language":"Python","stars":1418,"topics":["pytorch","tabular-data","text","images","multimodal-deep-learning","pytorch-tabular-data","pytorch-nlp","pytorch-cv","pytorch-transformers","deep-learning"],"license":"Apache-2.0","category":"machine-learning","readme_excerpt":"pytorch-widedeep A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch Documentation: https://pytorch-widedeep.readthedocs.io Companion posts and tutorials: infinitoml Experiments and comparison with LightGBM : TabularDL vs LightGBM Slack : if you want to contribute or just want to chat with us, join slack The content of this document is organized as follows: - pytorch-widedeep - Introduction - Architectures - The deeptabular component - The rec module - Text and Images - Installation - Developer Install - Quick start - Testing - How to Contribute - Acknowledgments - License - Cite - BibTex - APA Introduction pytorch-widedeep is based on Google's Wide and Deep Algorithm, adjusted for multi-modal datasets. In general terms, pytorch-widedeep is a package to use deep learning with tabular data. In particular, is intended to facilitate the combination of text and images with corresponding tabular data using wide and deep models. With that in mind there are a number of architectures that can be implemented with the library. The main components of those architectures are shown in the Figure below: In math terms, and following the notation in the paper, the expression for the architecture without a deephead component can be formulated as: 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 activatio","default_branch":null,"files":null,"tree":[],"storefront":"/r/jrzaurin","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/jrzaurin/pytorch-widedeep/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}