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vanilla-machine-learning
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ritchie46
5ae93a9a6a
lsh notebook
2020-05-15 10:36:15 +02:00
bayesian
add vae notebook
2020-03-27 09:33:43 +01:00
clustering
expectation_maximization
2019-05-24 13:31:53 +02:00
collaborative_filtering
svd tinkerings
2020-03-10 15:28:50 +01:00
ensembles
remove flaw from gbm code
2019-01-01 12:19:55 +01:00
gaussian_processes
add kernel information for gps in GPy notebook
2019-08-16 16:30:21 +02:00
generative-adversary-networks
dcgan
2018-07-17 12:03:41 +02:00
genetic_algorithms
Reasonable bridge. And validation almost working. Maybe binary tree adding?.
2018-01-04 18:17:43 +01:00
imputation
init svd imputer
2019-09-09 09:07:15 +02:00
linear_regression
policy network openai gym flagpole
2017-10-31 22:30:20 +01:00
logistic_regression
log regression formula update
2017-11-15 13:26:45 +01:00
nearest_neighbors
lsh notebook
2020-05-15 10:36:15 +02:00
neural_networks
refactor
2019-09-07 14:45:59 +02:00
reinforcement_learning
ga bridge
2017-12-26 13:48:09 +01:00
seq2seq
update seq2seq training
2019-02-20 11:40:27 +01:00
time_series
prophet pymc3 update
2018-10-10 17:03:02 +02:00
trainings
add variation inference training given to core team
2020-03-27 09:34:57 +01:00
.gitignore
don't ignore png files
2018-09-24 14:44:24 +02:00
readme.md
bayesian optimization finished
2019-09-07 14:36:50 +02:00
readme.md
Various machine learning algorithms. Mostly vanilla.
bayesian optimization
gaussian processes
bayesian generalized additive models
gradient boosting machines
dirichlet gaussian mixture models
affinity propagation
genetic algorithms
support vector machine
neural network
arima models
expectation maximization
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Readme
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