Deep Neural Net vs. Logistic Regression

This is a simple way to illustrate how a simple DNN can beat the performance of logistic regression in classification.

Release files for easy-dnn 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for easy-dnn 0.0.1
File	Size	Uploaded
easy_dnn-0.0.1.tar.gz	3.8 kB	Dec 13, 2020	Details

Table of built distributions (wheels) for easy-dnn 0.0.1
File	Interpreter	ABI	Platform	Reset
easy_dnn-0.0.1-py3-none-any.whl 4.8 kB Dec 13, 2020	Python 3	none	any	Details

Total release size: 8.6 kB

Download URL	easy_dnn-0.0.1.tar.gz
Size	3.8 kB
Tags	Source
SHA-256 checksum How to use checksums	`be751335222b2767266176b8f2825aa2619601365c5739dd5a2980bda1d16e16`
BLAKE2b-256 checksum How to use checksums	`36a9ce5b251a0516c528f8b25168e1004ee194ce249094f6254378dcd9f28ccb`
Upload date	Dec 13, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/51.0.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.9.0`

Download URL	easy_dnn-0.0.1-py3-none-any.whl
Size	4.8 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`4068a975bf2acb9bc3cb3dadd0cf5032f693c0791159338b572d3742d0467ff1`
BLAKE2b-256 checksum How to use checksums	`9fb35b8e5ef4c8ad3bf153afb8b56c122430fabf76d8a53d8ddce84eb64f0986`
Upload date	Dec 13, 2020
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/3.2.0 pkginfo/1.6.1 requests/2.25.0 setuptools/51.0.0 requests-toolbelt/0.9.1 tqdm/4.54.1 CPython/3.9.0`

This release

0.0.1 This release