DCT-Net
ydata-synthetic
DCT-Net | ydata-synthetic | |
---|---|---|
1 | 60 | |
712 | 1,324 | |
- | 5.1% | |
3.4 | 7.3 | |
7 months ago | 6 days ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
DCT-Net
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Alibaba AI Research Team Introduces ‘DCT-Net’; A Novel Image Translation Architecture For Few-Shot Portrait Stylization
Continue reading | Checkout the paper, project and github link
ydata-synthetic
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Coding Wonderland: Contribute to YData Profiling and YData Synthetic in this Advent of Code
Send us your North ⭐️: "On the first day of Christmas, my true contributor gave to me..." a star in my GitHub tree! 🎵 If you love these projects too, star ydata-profiling or ydata-synthetic and let your friends know why you love it so much!
- ydata-synthetic: NEW Data - star count:1083.0
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I absolutely hate my internship
1: Try to work with what you have and augment your dataset (honestly, 10 points is crap)
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Assessing the Quality of Synthetic Data with Data-Centric AI
Data Quality is key for all applications and models, and LLMs are no exception :) I've been working on a small community project with synthetic data (https://github.com/ydataai/ydata-synthetic) using ydata-synthetic, and it really shows! Underrepresentation (category imbalance) and missing data are two of the main issues!
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SOMEBODY HELP ME!
The Data-Centric AI Community creates community projects from time to time and is probably willing to help you in your project.
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Help for Data Scientist position
Join nice data communities and start networking.
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How to become a beast in DS ?
You know what they say: "Tell me who your friends are, and I'll tell you who you are!". Hang out with DS beasts and learn from them :)
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Hey guys, I have a few questions
Interesting question! I think our AI/ML devs at the Data-Centric AI Community could have nice perspectives for your to decide :)
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Embarking on a Journey of 99 Data Science Projects - From Beginner to Expert
Sounds like an amazing journey! Feel free to add your projects on our awesome-python-for-data-science repo as you go! And in case you need a hand or feedback on the projects, we'll be happy to help at the Data-Centric AI Community.
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Data science problems
The best to do is to get started with end-to-end projects in a collaborative environment (somewhat approaching real-world settings). You may find some interesting resources in this GitHub repository. The Data-Centric AI Community actually has a nice support system for this.
What are some alternatives?
stable-diffusion-reference-only - img2img version of stable diffusion. Anime Character Remix. Line Art Automatic Coloring. Style Transfer.
REaLTabFormer - A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022
Copulas - A library to model multivariate data using copulas.
cartoonify - Deploy and scale serverless machine learning app - in 4 steps.
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
faceswap-GAN - A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
Conditional-Sig-Wasserstein-GANs
ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]
pytorch-forecasting - Time series forecasting with PyTorch
stylegan-encoder - StyleGAN Encoder - converts real images to latent space
gretel-python-client - The Gretel Python Client allows you to interact with the Gretel REST API.