DeepEcho
Synthetic Data Generation for mixed-type, multivariate time series. (by sdv-dev)
trainer
Simple interface to synthesize complex and highly dimensional datasets using Gretel APIs. (by gretelai)
DeepEcho | trainer | |
---|---|---|
1 | 4 | |
88 | 28 | |
- | - | |
7.6 | 8.1 | |
4 days ago | 21 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
DeepEcho
Posts with mentions or reviews of DeepEcho.
We have used some of these posts to build our list of alternatives
and similar projects.
trainer
Posts with mentions or reviews of trainer.
We have used some of these posts to build our list of alternatives
and similar projects.
- Create safe, shareable data with Gretel Synthetics – in just a few clicks! Generate synthetic datasets with privacy guarantees for your PII data. Get started for free, http://gretel.ai
- [P] Training synthetic models on highly complex datasets
- Show HN: Training synthetic models on highly complex datasets
-
[P] Training synthetic models on highly complex datasets.
We published a notebook and a GitHub repo that helps you train synthetic models on highly dimensional datasets (e.g. 1000's of columns, and millions of records). It works by using Gretel's open source header clustering to group correlated data and parallelize training across multiple GPUs. https://github.com/gretelai/trainer
What are some alternatives?
When comparing DeepEcho and trainer you can also consider the following projects:
Anime-face-generation-DCGAN-webapp - A port of my Anime face generation using Pytorch into a Webapp
SDV - Synthetic data generation for tabular data
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.