creative-prediction
rtdl
creative-prediction | rtdl | |
---|---|---|
1 | 5 | |
23 | 314 | |
- | - | |
0.0 | 8.9 | |
over 1 year ago | about 2 years ago | |
Jupyter Notebook | Python | |
- | MIT License |
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creative-prediction
rtdl
-
[Project] Improving deep learning for tabular data with numerical embeddings (FT-Transformer)
Found relevant code at https://github.com/yandex-research/rtdl + all code implementations here
- [P] pytorch-widedeep v1.0.9: the Perceiver and the FastFormer for tabular data are now available in the library
- [P] pytorch-widedeep model alert: SAINT and the FT-Transformer are now available in the library
- [R] Revisiting Deep Learning Models for Tabular Data
What are some alternatives?
CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.
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vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
pytorch-widedeep - A flexible package for multimodal-deep-learning to combine tabular data with text and images using Wide and Deep models in Pytorch
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
100DaysofMLCode - My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge. Now supported by bright developers adding their learnings :+1:
edunn - Learn how modern, modular Neural Networks work by implementing a PyTorch/Keras-like framework.
ArtLine - A Deep Learning based project for creating line art portraits.
dopamine - Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.
best_AI_papers_2021 - A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
AI-Art-Generator - A program that can add an artistic touch to any image.
tabnet - PyTorch implementation of TabNet paper : https://arxiv.org/pdf/1908.07442.pdf