Pinned Repositories
cerebros
A NAS that is intended to more closely mimic a biological brain than conventional neural network strategies (under construction)
cerebros-core-algorithm-alpha
The Cerebros package is an ultra-precise Neural Architecture Search (NAS) / AutoML that is intended to much more closely mimic biological neurons than conventional neural network architecture strategies.
cerebros-enterprise-public
Public resources for Cerebros enterprise coutomers
class-example
A demo example for classes
cmdutil
A python utility for (sanely) running shell commands within a python script.
cpap-driver
A very basic driver for a last resort emergency CPAP
Cramspace
Cramspace Study Aid - "Don't waste time on questions you already know."
docs
The open-source repo for docs.github.com
github-actions-for-packages
python-rep-resampling
This takes any Pandas or Dask dataframe and returns a resampled Dask dataframe simulating the sampling distribution of your data in one line of code. This is like the rep_sample_n() function from the infer package in R, but on steroids and made for quickly simulating a large number of replicate samples and even with a large number of observations per sample rep. The dataframe it returns consists of 'n' observations per rep, 'rep' number of reps and is grouped by rep. Any aggregate operations you perform such as df['column'].mean().compute() or df['column'].std().compute() will run in parallel by default and give you an pandas series consisting of the means of each sample replicate. You can do most anything on this that you can with a Pandas DataFrame that is grouped by the same column. You just have to add the .compute() method to your method call, because this runs on futures parallelization. See the excerpts in the examples.
david-thrower's Repositories
david-thrower/cerebros-core-algorithm-alpha
The Cerebros package is an ultra-precise Neural Architecture Search (NAS) / AutoML that is intended to much more closely mimic biological neurons than conventional neural network architecture strategies.
david-thrower/cmdutil
A python utility for (sanely) running shell commands within a python script.
david-thrower/python-rep-resampling
This takes any Pandas or Dask dataframe and returns a resampled Dask dataframe simulating the sampling distribution of your data in one line of code. This is like the rep_sample_n() function from the infer package in R, but on steroids and made for quickly simulating a large number of replicate samples and even with a large number of observations per sample rep. The dataframe it returns consists of 'n' observations per rep, 'rep' number of reps and is grouped by rep. Any aggregate operations you perform such as df['column'].mean().compute() or df['column'].std().compute() will run in parallel by default and give you an pandas series consisting of the means of each sample replicate. You can do most anything on this that you can with a Pandas DataFrame that is grouped by the same column. You just have to add the .compute() method to your method call, because this runs on futures parallelization. See the excerpts in the examples.
david-thrower/cerebros
A NAS that is intended to more closely mimic a biological brain than conventional neural network strategies (under construction)
david-thrower/cerebros-enterprise-public
Public resources for Cerebros enterprise coutomers
david-thrower/class-example
A demo example for classes
david-thrower/cpap-driver
A very basic driver for a last resort emergency CPAP
david-thrower/Cramspace
Cramspace Study Aid - "Don't waste time on questions you already know."
david-thrower/docs
The open-source repo for docs.github.com
david-thrower/github-actions-for-packages
david-thrower/hello-github-actions
david-thrower/keras-EfficientNetB7-transfer-learning-base-model
A transfer learning amenable version of EfficientNetB7
david-thrower/residual_MLP_Tests
Tests I am performing on a Python package for building residual multi - layer perceptrons and tandem [any model] -> ResMLPs models, useful for effective transfer learning. A pypi package should be coming soon.
david-thrower/mlops-on-gcp
david-thrower/multimedia-classifier-clouds-dummy-training-data
A data set to benchmark test a multimedia classification NAS algo meant for small multimedia data sets.
david-thrower/test-k3s
Test using k3s
david-thrower/ValidatesAll-1.0
This is a function that can be used to validate all sorts of restrictions on a field's input ...