autovideo
autokeras
autovideo | autokeras | |
---|---|---|
2 | 5 | |
310 | 9,067 | |
-0.3% | 0.2% | |
4.9 | 5.3 | |
11 months ago | about 2 months ago | |
Python | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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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.
autovideo
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AutoVideo: An Automated Video Action Recognition System
Code for https://arxiv.org/abs/2108.04212 found: https://github.com/datamllab/autovideo
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DATA Lab at Texas A&M University presents AutoVideo: An Automated Video Action Recognition System
GitHub: https://github.com/datamllab/autovideo
autokeras
- Machine Learning Algorithms Cheat Sheet
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Ask HN: Which piece of tech is underutilized?
I think the interfaces aren't high level enough for the average programmer to adopt it. It needs what https://autokeras.com is for neural nets.
- Technical documentation that just works
- SVM training taking forever on my local machine. Will using AWS Sagemaker be faster for training SVM (Linear) models?
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[D] [P] How do you use tools like AutoML?
AutoKeras time_series_forecaster.py
What are some alternatives?
MoViNet-pytorch - MoViNets PyTorch implementation: Mobile Video Networks for Efficient Video Recognition;
autogluon - Fast and Accurate ML in 3 Lines of Code
autoalbument - AutoML for image augmentation. AutoAlbument uses the Faster AutoAugment algorithm to find optimal augmentation policies. Documentation - https://albumentations.ai/docs/autoalbument/
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
adanet - Fast and flexible AutoML with learning guarantees.
tf-keras-vis - Neural network visualization toolkit for tf.keras
automlbenchmark - OpenML AutoML Benchmarking Framework
AutoViz - Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
NAS-Projects - Automated deep learning algorithms implemented in PyTorch. [Moved to: https://github.com/D-X-Y/AutoDL-Projects]
deephyper - DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
sphinx - The Sphinx documentation generator