A Package for Neural Networks for Beginners and Professionals
Project description
Introduction to usito
This package is provided by researchers of the Institute of Applied Optics (University of Stuttgart). It enables students and fellow researchers a simple introduction into neural networks and allows the generic use of those networks. The package shall also grow over time, that we can provide more sophisticated architectures and modified class methods (e.g. for layers or activation functions).
Our development is (at least currently) solely based on the keras and tensorflow engine.
Participation is welcomed.
Welcome to the ITO family. Plug in and play :)
Your developers and maintainers, AliB and FelixFischer
How to get started
#importing the package
import usito
#loading example
data = usito.load('./test.csv', header = 0)
ToDos:
[x] Data import and export [x] Zipping and unzipping option [ ] Creating pip package for usito
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file usito-0.0.2.tar.gz.
File metadata
- Download URL: usito-0.0.2.tar.gz
- Upload date:
- Size: 15.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8d853c4579e3728a7af4dab9f3ecc90f540b39b2911d4fdffcc5967e19e9ff43
|
|
| MD5 |
93c8cd144c271389f129f1bd4be99280
|
|
| BLAKE2b-256 |
76f9bbf93a716cc6c958345edfa3a0ab0088d5ef2565feae60733df6bcb456a3
|
File details
Details for the file usito-0.0.2-py3-none-any.whl.
File metadata
- Download URL: usito-0.0.2-py3-none-any.whl
- Upload date:
- Size: 19.8 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.6.4 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.9.6
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
eba05b805aa6b9cfdb5b240164a65c58062a3303889bfdfd104cbe1fcad9a474
|
|
| MD5 |
b25b0519729763d06a63c07a4d693f16
|
|
| BLAKE2b-256 |
c0956e0635738908f67710306d25737d579d9405403870912232e0c9d9154bc9
|