wtte-rnn VS nni

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

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

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 nni
3 5
759 13,765
- 0.5%
0.0 6.7
over 3 years ago about 2 months 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.

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.

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.

What are some alternatives?

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

easyesn - Python library for Reservoir Computing using Echo State Networks

optuna - A hyperparameter optimization framework

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

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

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

autogluon - Fast and Accurate ML in 3 Lines of Code

providence

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

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

hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python

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

automlbenchmark - OpenML AutoML Benchmarking Framework

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