pypredictor
The Python library that makes AI predictions simple.
View the GitHub Page
What can it do?
pypredictor uses an RNN (Recurrent Neural Network) to predict the next n numbers in a sequence. As an example, using this code:
pred = NumPredictor(500)
print(pred.predict([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 5, 3))
pypredictor generated the following output, which is quite accurate:
[10.969043, 11.950292, 12.920968, 13.859894, 14.789316]
pypredictor also has the ability to generate a pandas DataFrame and a seaborn line graph, from an initial sequence/DataFrame which you provide.
Plus, there are examples in the examples/ directory, so you can take a look for yourself :)
How to install
Install via pip:
$ pip install pypredictor
To get examples, clone this repository and enter pypredictor/examples:
$ git clone https://github.com/hamdivazim/pypredictor.git
$ cd pypredictor/examples
anaconda support hopefully coming soon!
License
pypredictor is licensed by Hamd Waseem (codingboy_CW) under the Apache License 2.0.
2 maintainers
Metadata
2 maintainers
Release files for pypredictor 0.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pypredictor-0.1.1.tar.gz | 8.2 kB | Without provenance | Details for pypredictor-0.1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| pypredictor-0.1.1-py3-none-any.whl | Python 3 | none | any | Details for pypredictor-0.1.1-py3-none-any.whl |
Total release size: 17.5 kB
Release files / pypredictor-0.1.1.tar.gz
| Download URL | pypredictor-0.1.1.tar.gz |
|---|---|
| Size | 8.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
f1fbcaf894d7e582390d5dd727571b53c4fae7fa27f5cdd2814b3a811a310b25
|
|
BLAKE2b-256 checksum How to use checksums |
174ecd67ac6a1a18c0e5ba3f639c27b4622dfcf649250031fca225a3353db8fb
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.5
|
Release files / pypredictor-0.1.1-py3-none-any.whl
| Download URL | pypredictor-0.1.1-py3-none-any.whl |
|---|---|
| Size | 9.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3e94603c53bb95d7988e3f4750393a420f6a0cb53b3b8be9e1dfd89787cdf20e
|
|
BLAKE2b-256 checksum How to use checksums |
9c4cb3519dc8211bcb4c3a4deb10ac28117a820588c70054b0732f7ac38aa676
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.1 CPython/3.10.5
|
Security for pypredictor 0.1.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
