#
hyperparameter-search
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eddiebergman
commented
Jan 10, 2022
We currently fit and predict upon loading autosklearn.experimental.askl2 for the first time. In environments with a non-persistent filesystem (autosklearn is installed into a new filesystem each time), this can add quite a bit of time delay as experienced in #1362
It seems more applicable to export the
data-science
machine-learning
reinforcement-learning
deep-learning
tensorflow
keras
collaboration
pytorch
hyperparameter-optimization
reproducibility
hyperparameter-tuning
data-versioning
hyperparameter-search
model-versioning
mlops
experiment-track
ml-platform
-
Updated
Apr 9, 2022 - Python
Sequential model-based optimization with a `scipy.optimize` interface
visualization
machine-learning
binder
optimization
scikit-learn
scientific-visualization
scientific-computing
hyperparameter-optimization
bayesopt
gradient
bayesian-optimization
hacktoberfest
hyperparameter-tuning
hyperparameter
hyperparameter-search
sequential-recommendation
-
Updated
Feb 3, 2022 - Python
Determined: Deep Learning Training Platform
kubernetes
data-science
machine-learning
deep-learning
tensorflow
pytorch
hyperparameter-optimization
hyperparameter-tuning
hyperparameter-search
distributed-training
ml-infrastructure
mlops
ml-platform
-
Updated
Apr 8, 2022 - Python
A collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
reinforcement-learning
optimization
openai-gym
hyperparameters
openai
gym
hyperparameter-optimization
rl
zoo
hyperparameter-tuning
hyperparameter-search
pybullet
stable-baselines
-
Updated
Feb 6, 2021 - Python
PaddleSlim is an open-source library for deep model compression and architecture search.
pruning
quantization
nas
knowledge-distillation
evolution-strategy
model-compression
neural-architecture-search
hyperparameter-search
autodl
-
Updated
Apr 8, 2022 - Python
Sequential Model-based Algorithm Configuration
random-forest
configuration
hyperparameter-optimization
bayesian-optimization
hyperparameter-tuning
automl
automated-machine-learning
hyperparameter-search
bayesian-optimisation
gaussian-process
algorithm-configuration
-
Updated
Apr 7, 2022 - Python
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
reinforcement-learning
robotics
optimization
lab
openai
gym
hyperparameter-optimization
rl
sde
hyperparameter-tuning
hyperparameter-search
pybullet
stable-baselines
pybullet-environments
tuning-hyperparameters
-
Updated
Apr 9, 2022 - Python
guillaume-chevalier
commented
Jun 28, 2021
Describe the bug
Code could be more conform to pep8 and so forth.
Expected behavior
Less code st
OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)
nlp
natural-language-processing
hyperparameter-optimization
topic-modeling
nlp-library
bayesian-optimization
hyperparameter-tuning
latent-dirichlet-allocation
evaluation-metrics
neural-topic-models
latent-semantic-analysis
topic-models
hyperparameter-search
non-negative-matrix-factorization
nlproc
-
Updated
Feb 26, 2022 - Python
Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.
machine-learning
deep-learning
keras
hyperparameter-optimization
machine-learning-library
bayesian-optimization
hyperparameter-tuning
hyperparameter-search
hyperparameter-grid
-
Updated
Oct 18, 2020 - JavaScript
Library for Semi-Automated Data Science
python
data-science
machine-learning
scikit-learn
artificial-intelligence
interoperability
hyperparameter-optimization
hyperparameter-tuning
ibm-research
automl
automated-machine-learning
dataquality
hyperparameter-search
ibm-research-ai
pipeline-tests
pipeline-testing
-
Updated
Apr 9, 2022 - Python
DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks
python
deep-neural-networks
tensorflow
scalability
keras
ml
neural-networks
hyperparameter-optimization
supercomputers
automl
neural-architecture-search
hyperparameter-search
autodl
-
Updated
Mar 31, 2022 - Python
Population Based Training (in PyTorch with sqlite3). Status: Unsupported
deep-learning
hyperparameters
hyperparameter-optimization
deepmind
hyperparameter-tuning
pbt
hyperparameter-search
population-based-training
-
Updated
Jan 31, 2018 - Python
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
tensorflow
keras
cnn
hyperparameter-optimization
hyperopt
hyperparameters-optimization
hyperparameter-tuning
cnn-keras
hyperparameter-search
-
Updated
May 6, 2018 - Python
Black-box optimization library
-
Updated
Jan 11, 2022 - Jupyter Notebook
Distribution transparent Machine Learning experiments on Apache Spark
spark
hyperparameter-optimization
hyperparameter-tuning
automl
hyperparameter-search
blackbox-optimization
ablation
ablation-studies
ablation-study
-
Updated
Mar 28, 2022 - Python
python
anaconda
imagenet
convolutional-neural-networks
hyperparameter-search
tiny-imagenet200
tiny-imagenet
-
Updated
Apr 12, 2019 - Python
Hyperparameter search for AllenNLP - powered by Ray TUNE
-
Updated
Oct 7, 2019 - Python
AutoML - Hyper parameters search for scikit-learn pipelines using Microsoft NNI
tool
scikit-learn
sklearn
hyperparameters
automl
scikit-learn-api
hyperparameter-search
sklearn-library
nni
neural-network-intelligence
-
Updated
Oct 21, 2021 - Python
An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning 🚀
machine-learning
recommender-system
hyperopt
hyperparameter-tuning
automl
automated-machine-learning
hyperparameter-search
surprise
tpe
-
Updated
Mar 25, 2022 - Python
machine-learning
deep-learning
scikit-learn
keras
artificial-intelligence
hyperparameter-search
hyperas
-
Updated
May 13, 2019 - Jupyter Notebook
sharpDARTS: Faster and More Accurate Differentiable Architecture Search
computer-vision
deep-learning
pytorch
neural-networks
hyperparameter-optimization
imagenet
nas
hyperparameter-tuning
learning-rate
cifar10
sota
neural-architecture-search
hyperparameter-search
state-of-the-art
architecture-search
cosine-annealing
learning-rate-scheduling
differentiable-hyperparamter-search
cosine-power-annealing
power-cosine-annealing
-
Updated
Feb 7, 2021 - Python
Hyperparameters-Optimization
optimization
hyperparameter-optimization
grid-search
bayesian-optimization
hyperparameter-tuning
random-search
hpo
hyperparameter
hyperparameter-search
tpe
gridsearchcv
hyperband
tree-structured
randomsearchcv
hyperbandsearchcv
bayessearchcv
fmin
tree-of-parzen-estimator
-
Updated
Nov 16, 2020 - Jupyter Notebook
Platform + GUI for hyperparameter optimization of recurrent neural networks (MATLAB).
gui
matlab
recurrent-networks
hyperparameter-optimization
rnn
hyperparameter-tuning
parallel-processing
hyperparameter-search
neural-network-architectures
-
Updated
Dec 29, 2021 - MATLAB
Sentiment analysis for amazon product reviews using NLTK, Scikit-Learn, and Keras. Using hyperparameter search and LSTM, our best model achieves ~96% accuracy.
machine-learning
natural-language-processing
sentiment-analysis
scikit-learn
keras
lstm
nltk
bag-of-words
binary-classification
tokenize
sequence-models
hyperparameter-search
-
Updated
Sep 24, 2019 - Python
sklearn wrapper for Hyperopt
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Updated
Oct 9, 2019 - Python
hyperparameter search for machine learning
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Updated
Oct 31, 2017 - Python
The objective of the dataset is to diagnostically predict whether or not a patient has diabetes, based on certain diagnostic measurements included in the dataset
histogram
feature-selection
adaboost
evaluation-metrics
hyperparameter-search
feature-importance
random-forest-classifier
pairplot
randomized-search
svc-svm
-
Updated
Feb 22, 2019 - Jupyter Notebook
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the
ci/travisfolder is confusing. Theci/README.mdalso mentions Travis, could be interpreted in all sorts of ways. maybe time to change that to something more agnostic? After all, we're not using Travis anymore.Use case