Multilayered Perceptron By Pranav Sai:
#Network 2=InputSize,3=HiddenSize, 1=OutputSize
net=Network(2,3,1)
#Traning Data : training_inputs= hours slept,hours studied ; training_outputs= Grade of Test training_inputs = np.array(([2, 9], [1, 5], [3, 6]), dtype=float)
training_outputs = np.array(([92], [86], [89]), dtype=float)
net.train(training_inputs,training_outputs,1000)
print(“Predicted Output: “ + str(net.run([2,3])))
CHANGELOG
0.0.1(2/27/2022)
-First Release: Multilayered Perception
1 maintainer
Release files for NeuNetMlp 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| NeuNetMlp-0.0.4.tar.gz | 3.0 kB | Details |
Release files / NeuNetMlp-0.0.4.tar.gz
| Download URL | NeuNetMlp-0.0.4.tar.gz |
|---|---|
| Size | 3.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
8aff90569a87fa7f94d3267e5cdf0706690394583e87e03df6dac65434c282b6
|
|
BLAKE2b-256 checksum How to use checksums |
5e3e80ad82487bc260bc065de2f151da3961e643b722b8c390b07f1d23952b63
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.8.0 pkginfo/1.8.2 readme-renderer/30.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.7 tqdm/4.62.3 importlib-metadata/4.8.1 keyring/23.2.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.10.0
|
