The On-Ramp to Deep Learning
Built in Python 3 on Keras 2.
Read the documentation at conx.readthedocs.io
Ask questions on the mailing list: conx-users
Implements Deep Learning neural network algorithms using a simple interface with easy visualizations and useful analytics. Built on top of Keras, which can use either TensorFlow, Theano, or CNTK.
A network can be specified to the constructor by providing sizes. For example, Network(“XOR”, 2, 5, 1) specifies a network named “XOR” with a 2-node input layer, 5-unit hidden layer, and a 1-unit output layer. However, any complex network can be constructed using the net.connect() method.
Computing XOR via a target function:
import conx as cx
dataset = [[[0, 0], [0]],
[[0, 1], [1]],
[[1, 0], [1]],
[[1, 1], [0]]]
net = cx.Network("XOR", 2, 5, 1, activation="sigmoid")
net.dataset.load(dataset)
net.compile(error='mean_squared_error',
optimizer="sgd", lr=0.3, momentum=0.9)
net.train(2000, report_rate=10, accuracy=1.0)
net.test(show=True)Creates dynamic, rendered visualizations like this:
Examples
See conx-notebooks and the documentation for additional examples.
Installation
1 maintainer
Metadata
1 maintainer
Release files for conx 3.7.10
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| conx-3.7.10.tar.gz | 105.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| conx-3.7.10-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size: 214.8 kB
Release files / conx-3.7.10.tar.gz
| Download URL | conx-3.7.10.tar.gz |
|---|---|
| Size | 105.0 kB |
| Tags | Source |
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Release files / conx-3.7.10-py2.py3-none-any.whl
| Download URL | conx-3.7.10-py2.py3-none-any.whl |
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| Size | 109.8 kB |
| Tags | Python 2 Python 3 |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.19.1 setuptools/39.1.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.6.7
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