nni VS wtte-rnn

Compare nni vs wtte-rnn and see what are their differences.

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. (by microsoft)
Automl Deep Learning neural-architecture-search hyperparameter-optimization Distributed bayesian-optimization automated-machine-learning Machine Learning machine-learning-algorithms Data Science Tensorflow Pytorch neural-network deep-neural-network model-compression feature-engineering Nas Python hyperparameter-tuning Mlops
Source Code
nni.readthedocs.io
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wtte-rnn

WTTE-RNN a framework for churn and time to event prediction (by ragulpr)
weibull machine-learning-algorithms Tensorflow Rnn Keras neural-network churn-prediction failure-rate
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nni wtte-rnn
5 3
13,726 756
0.9% -
6.7 0.0
about 2 months ago over 3 years ago
Python Python
MIT License MIT License
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.

nni

Posts with mentions or reviews of nni. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-04.

wtte-rnn

Posts with mentions or reviews of wtte-rnn. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-24.

What are some alternatives?

When comparing nni and wtte-rnn you can also consider the following projects:

optuna - A hyperparameter optimization framework

easyesn - Python library for Reservoir Computing using Echo State Networks

FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

GLOM-TensorFlow - An attempt at the implementation of GLOM, Geoffrey Hinton's paper for emergent part-whole hierarchies from data

autogluon - AutoGluon: Fast and Accurate ML in 3 Lines of Code

neptune-client - 📘 The MLOps stack component for experiment tracking

AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]

providence

hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python

image-super-resolution - 🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.

automlbenchmark - OpenML AutoML Benchmarking Framework

nni vs optuna wtte-rnn vs easyesn nni vs FLAML wtte-rnn vs GLOM-TensorFlow nni vs autogluon wtte-rnn vs neptune-client nni vs AutoML wtte-rnn vs providence nni vs hyperopt wtte-rnn vs image-super-resolution nni vs archai nni vs automlbenchmark