synthetic-data-genomics
ydata-synthetic
synthetic-data-genomics | ydata-synthetic | |
---|---|---|
3 | 60 | |
32 | 1,324 | |
- | 5.1% | |
0.0 | 7.3 | |
over 2 years ago | 8 days ago | |
Jupyter Notebook | Jupyter Notebook | |
- | 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.
synthetic-data-genomics
- Show HN: Synthetic Data Genomics
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[P] Synthetic Data Genomics
This is the proof of concept code from a Gretel.ai & Illumina project that used generative neural networks to create synthetic versions of mouse genotype and phenotype data. https://github.com/gretelai/synthetic-data-genomics
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Using AI to create safe, synthetic datasets for genomics
The code in this repository uses Gretel.ai's synthetic data APIs to create synthetic (artificial) versions of real world mouse genotype and connected phenotype datasets. https://doi.org/10.1038/ng.3609. https://github.com/gretelai/synthetic-data-genomics
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?
genalog - Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.
REaLTabFormer - A suite of auto-regressive and Seq2Seq (sequence-to-sequence) transformer models for tabular and relational synthetic data generation.
Copulas - A library to model multivariate data using copulas.
DeepRL-TensorFlow2 - 🐋 Simple implementations of various popular Deep Reinforcement Learning algorithms using TensorFlow2
Conditional-Sig-Wasserstein-GANs
pytorch-forecasting - Time series forecasting with PyTorch
gretel-python-client - The Gretel Python Client allows you to interact with the Gretel REST API.
Robotics-Object-Pose-Estimation - A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
Spectrum - Spectrum is an AI that uses machine learning to generate Rap song lyrics
GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data
machine-learning-for-trading - Code for Machine Learning for Algorithmic Trading, 2nd edition.
awesome-data-centric-ai - Open-Source Software, Tutorials, and Research on Data-Centric AI 🤖