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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

hello-github-actions

keras-efficientnetb7-transfer-learning-base-model

A transfer learning amenable version of EfficientNetB7

mlops-on-gcp

multimedia-classifier-clouds-dummy-training-data

A data set to benchmark test a multimedia classification NAS algo meant for small multimedia data sets.

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.

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.

test-k3s

Test using k3s

validatesall-1.0

This is a function that can be used to validate all sorts of restrictions on a field's input ...