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Nov 11, 2019 - Jupyter Notebook
#
hyperparameters
Here are 60 public repositories matching this topic...
Open-source implementation of Google Vizier for hyper parameters tuning
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
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Aug 4, 2020 - Python
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
deep-learning
neural-network
reproducible-research
collaborative-filtering
matrix-factorization
hyperparameters
bpr
recommendation-system
recommender-system
reproducibility
recommendation-algorithms
knn
matrix-completion
evaluation-framework
content-based-recommendation
hybrid-recommender-system
funksvd
bprmf
bprslim
slimelasticnet
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Aug 7, 2020 - Python
Tuning hyperparams fast with Hyperband
machine-learning
hyperparameters
hyperparameter-optimization
hyperparameter-tuning
gradient-boosting-classifier
gradient-boosting
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Aug 15, 2018 - Python
Population Based Training (in PyTorch with sqlite3). Status: Unsupported
deep-learning
hyperparameters
hyperparameter-optimization
deepmind
hyperparameter-tuning
pbt
hyperparameter-search
population-based-training
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Jan 31, 2018 - Python
Workflow engine for exploration of simulation models using high throughput computing
workflow
scala
grid
workflow-engine
distributed-computing
hyperparameters
scientific-computing
parameter-estimation
modeling-tool
parameter-search
egi
parameter-tuning
dirac
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Aug 19, 2020 - Scala
A thoughtful approach to hyperparameter management.
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Jun 20, 2020 - Python
Adventures using keras on Google's Cloud ML Engine
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May 18, 2017 - Python
Streamlined machine learning experiment management.
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Apr 27, 2020 - HTML
csala
commented
Jan 28, 2020
Current save/load methods focus on dumping and loading the pipeline definition in its JSON form, but provide no means to save a fitted pipeline and load it later to make predictions, being the usage of pickle outside of the pipeline the only way to go.
Let's re-implement the save/load methods to save the whole pipeline instance, and move the current save functionality to a to_json method.
Purely functional genetic algorithms for multi-objective optimisation
scala
functional-programming
genetic-algorithm
hyperparameters
hyperparameter-optimization
hyperparameter-tuning
optimisation
parameter-tuning
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Jul 9, 2020 - Scala
Machine learning algorithms in Dart programming language
dart
classifier
data-science
machine-learning
algorithm
linear-regression
machine-learning-algorithms
regression
hyperparameters
sgd
logistic-regression
softmax-regression
dartlang
stochastic-gradient-descent
softmax
lasso-regression
batch-gradient-descent
mini-batch-gradient-descent
softmax-classifier
softmax-algorithm
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Aug 16, 2020 - Dart
Easily declare large spaces of (keras) neural networks and run (hyperopt) optimization experiments on them.
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Feb 6, 2017 - Python
Deep learning, architecture and hyper parameters search with genetic algorithms
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Sep 14, 2017 - Python
How to initialize Anchors in Faster RCNN for custom dataset?
python
computer-vision
aspect-ratio
detection
hyperparameters
anchor
faster-rcnn
object-detection
kmeans
clusters
distance-metric
bounding-boxes
tensorflow-models
iou
custom-dataset
anchor-box
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Aug 18, 2020 - Jupyter Notebook
ES6 hyperparameters search for tfjs
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Dec 24, 2018 - JavaScript
Automatic and Simultaneous Adjustment of Learning Rate and Momentum for Stochastic Gradient Descent
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Aug 4, 2020 - Python
A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python
python
machine-learning
r
h2o
prediction
artificial-intelligence
hyperparameters
forecasting
gbm
ensemble
satellite-imagery
modis
drought
ensemble-model
landuse
vegetation-health
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Apr 13, 2016 - Python
Tuning XGBoost hyper-parameters with Simulated Annealing
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Apr 26, 2017 - Jupyter Notebook
Spark Parameter Optimization and Tuning
machine-learning
spark
optimizer
hyperparameters
hyperparameter-optimization
machinelearning
vowpal-wabbit
grid-search
hyperparameter-tuning
random-search
optimization-algorithms
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Apr 11, 2018 - Scala
How optimizer and learning rate choice affects training performance
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Apr 12, 2018 - Python
ParamHelpers Next Generation
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Aug 19, 2020 - R
OptKeras: wrapper around Keras and Optuna for hyperparameter optimization
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Apr 1, 2020 - 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
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Mar 31, 2020 - Python
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Jan 4, 2019 - Jupyter Notebook
Using DDPG and A2C reinforcement learning algorithms to solve a math puzzle
reinforcement-learning
ai
puzzle
deep-learning
neural-network
artificial-intelligence
hyperparameters
ddpg
actor-critic
a2c
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Sep 3, 2019 - Python
Introductory Kaggle competition
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Jun 13, 2016 - Jupyter Notebook
Argload, easy reloading of command line arguments
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May 9, 2018 - Python
A library for the hyperparameter optimization of deep neural networks
python
deep-neural-networks
optimization
pytorch
hyperparameters
hyperparameter-optimization
nomad
hyperparameter-tuning
neural-architecture-search
categorical-variables
blackbox-optimization
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Jul 17, 2020 - C++
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