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cross-validation
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scikit-learn cross validators for iterative stratification of multilabel data
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Sep 12, 2020 - Python
Machine learning for C# .Net
learning
machine-learning
opensource
deep-learning
csharp
dotnet
random-forest
metrics
machine
cross-validation
gradient-boosting-machine
ensemble-learning
adaboost
decision-trees
neural-nets
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Jul 12, 2020 - C#
A Portfolio of my Data Science Projects
finance
data-science
jupyter-notebook
cross-validation
regression
data-visualization
data-analysis
rmarkdown-document
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Oct 8, 2019 - Jupyter Notebook
Time Series Cross-Validation -- an extension for scikit-learn
data-science
machine-learning
time-series
cross-validation
model-selection
hyperparameter-optimization
tuning-parameters
backtesting
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Feb 20, 2020 - Python
Machine Learning with the NSL-KDD dataset for Network Intrusion Detection
machine-learning
random-forest
cross-validation
feature-selection
decision-trees
datamining
intrusion-detection-system
network-intrusion-detection
kdd99
nsl-kdd
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Apr 5, 2020 - Jupyter Notebook
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
cross-validation
bayesian-methods
stan
r-package
bayesian-data-analysis
model-comparison
information-criterion
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Jul 29, 2020 - R
State-of-the art Automated Machine Learning python library for Tabular Data
python
data-science
machine-learning
sklearn
cross-validation
ml
model-selection
xgboost
hyperparameter-optimization
machine-learning-library
hyperparameter-tuning
optimisation
automl
stacking
auto-ml
machine-learning-models
automatic-machine-learning
data-science-projects
stacking-ensemble
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Aug 5, 2020 - Python
Easy and comprehensive assessment of predictive power, with support for neuroimaging features
machine-learning
scikit-learn
cross-validation
report
easy-to-use
neuroimaging
pattern-recognition
nilearn
tractography
structural-imaging
anatomical-mri
functional-connectivity
tract-based-statistics
resting-state
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Jul 13, 2020 - Python
Automated rejection and repair of bad trials/sensors in M/EEG
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Jul 10, 2020 - Python
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
wrapper
data-science
time-series
sklearn
parallel
cross-validation
transformer
model-selection
statsmodels
wrapper-library
sklearn-compatible
fbprophet
sarimax
time-series-forecasting
sklearn-library
sklearn-api
pmdarima
tbats
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Sep 14, 2020 - Python
python
machine-learning
optimization
scikit-learn
models
cross-validation
hyperparameter-optimization
pretty-logo
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Apr 19, 2019 - Python
Useful functions to work with PyTorch. At the moment, there is a function to work with cross validation and kernels visualization.
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May 29, 2020 - Python
LIBSVM for the browser and nodejs 🔥
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Mar 20, 2019 - JavaScript
Hyperparameter tuning for machine learning models using a distributed genetic algorithm
machine-learning
rabbitmq
genetic-algorithm
keras
cross-validation
xgboost
hyperparameter-optimization
convolutional-neural-networks
genetic-algorithms
grid-search
hyperparameter-tuning
distributed-algorithm
master-worker
gene-encoding
distributed-genetic-algorithm
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Mar 7, 2020 - Python
subsemble R package for ensemble learning on subsets of data
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Aug 1, 2017 - R
SuperLearner guide: fitting models, ensembling, prediction, hyperparameters, parallelization, timing, feature selection, etc.
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Apr 17, 2019 - HTML
R package cross-validation, bootstrap, permutation, and rolling window resampling techniques for the tidyverse.
bootstrap
tidyverse
cross-validation
permutation
jackknife
resampling-methods
rolling-windows
modelr
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Jul 22, 2018 - R
pytorch implementation of paper https://www.frontiersin.org/articles/10.3389/fcomp.2020.00035/full
machine-learning
computer-vision
graph-algorithms
cross-validation
pytorch
convolutional-neural-networks
unet
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image-procesing
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u-net
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fundus-image
pytorch-vizualization
retinal-vessel-segmentation
universal-pytorch-framework
centralized-image-processing
custom-data-loader-pytorch
custom-dataloader
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Jul 30, 2020 - Jupyter Notebook
machine-learning
deep-learning
tensorflow
cross-validation
python3
convolutional-neural-networks
handwritten-text-recognition
ctc-loss
lstm-networks
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Apr 16, 2018 - Python
The implementation of 3D-UNet using PyTorch
cross-validation
pytorch
unet
semantic-segmentation
volumetric-data
3d-segmentation
pytorch-implementation
3d-unet
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Feb 12, 2020 - Python
Machine learning toolkits with Python
python
bootstrap
machine-learning
metrics
scikit-learn
evaluation
cross-validation
ensemble
ensemble-learning
roc
grid-search
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Oct 7, 2017 - Jupyter Notebook
Spatio-temporal resampling methods for mlr3
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Sep 14, 2020 - R
Use the famous CIFAR-10 dataset to train a multi-layer neural network to recognize images of cats, dogs, and other things.
php
machine-learning
tutorial
deep-neural-networks
computer-vision
deep-learning
neural-network
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computer
image-classification
image-recognition
object-detection
example-project
cifar-10
php-ml
machine-learning-tutorial
rubix-ml
php-machine-learning
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Aug 7, 2020 - PHP
Configurable Naive Bayes Classifier for text with cross-validation support
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Aug 14, 2019 - JavaScript
All codes, both created and optimized for best results from the SuperDataScience Course
natural-language-processing
reinforcement-learning
deep-learning
clustering
cross-validation
naive-bayes-classifier
thompson-sampling
neural-networks
classification
dimensionality-reduction
grid-search
principal-component-analysis
clustering-algorithm
upper-confidence-bounds
k-fold
xgboost-algorithm
association-rule-learning
machine-learning-az
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Nov 5, 2017 - Python
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization
nlp
machine-learning
sentiment-analysis
cross-validation
eda
data-visualization
wordcloud
classification
data-analysis
bag-of-words
hashtags
evaluation-metrics
count-vectorizer
datacleaning
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May 14, 2019 - Jupyter Notebook
An Interactive Approach to Understanding Deep Learning with Keras
machine-learning
tensorflow
scikit-learn
keras
cross-validation
regression
classification
artificial-neural-networks
logistic-regression
regularization
support-vector-machine
vectors
decision-trees
hyperparameter-tuning
model-evaluation
magnetic-resonance-imaging
k-means-clustering
model-tuning
scalars
linear-transformation
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Sep 6, 2020 - Jupyter Notebook
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Unlike N-Gram, the current Skip-Gram tokenizer does not allow variable length tokens. This ticket is to implement a min max scheme similar to the N-Gram tokenizer such that each token is a k-skip-n-gram. In other words, instead of fi