Machine Learning And Deep Learning Algorithms from Scratch
In this repository, major machine learning and deep learning algorithms are implemented from scratch. From scratch meaning without using external machine learning libraries. All of the below mentioned algorithms are implemented in Python, Linear Regression is also implemented in C++. The API structure is similar to the Scikit-Learn library and Tensorflow Keras API.
Algorithms:
Supervised Learning:
Unsupervised Learning:
Deep Learning:
Neural Networks added with ReLU, Softmax Activations and Categorical Cross Entropy losses, and Optimizers such as SGD, Adam.
To use this implementation:
pip install open-nn-python
Release files for AgainML 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 | |
|---|---|---|---|
| AgainML-0.1.1.tar.gz | 7.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| AgainML-0.1.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 15.3 kB
Release files / AgainML-0.1.1.tar.gz
| Download URL | AgainML-0.1.1.tar.gz |
|---|---|
| Size | 7.4 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Release files / AgainML-0.1.1-py3-none-any.whl
| Download URL | AgainML-0.1.1-py3-none-any.whl |
|---|---|
| Size | 7.9 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.10.8
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