Metadata-Version: 2.1
Name: mlalgs
Version: 0.0.2
Summary: Machine Learning Algorithms from Scratch in Python
Home-page: http://www.amirhessam.com
Author: Amirhessam Tahmassebi
Author-email: amir.benny@gmail.com
License: MIT
Download-URL: https://github.com/amirhessam88/ml-algs/
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        <p align="center">
        <a href="https://www.amirhessam.com/">
          <img src="https://raw.githubusercontent.com/amirhessam88/ml-algs/master/assets/design/logo.png" width="250"></img></a>
        </p>
        
        <h1 align="center">
            Machine Learning Algorithms from Scratch in Python
        </h1>
        
        
        ## Installation
        
        First, install Python 3.6 from https://www.python.org, and then run:
        
        ```
        pip install mlalgs
        ```
        
        ## Implementations
        - **Logistic Regression:** [Source](mlalgs/logistic_regression.py), [Notebook](notebooks/logistic_regression.ipynb)
        
        ## Citation
        If you use the library in academic work, please consider citing
        https://doi.org/10.1117/12.2304418 .
        
        ### Bibtex Entry:
        ```bib
        @inproceedings{tahmassebi2018ideeple,
          title={ideeple: Deep learning in a flash},
          author={Tahmassebi, Amirhessam},
          booktitle={Disruptive Technologies in Information Sciences},
          volume={10652},
          pages={106520S},
          year={2018},
          organization={International Society for Optics and Photonics}
        }
        ```
        ### APA Entry:
        
        Tahmassebi, A. (2018, May). ideeple: Deep learning in a flash. In Disruptive
        Technologies in Information Sciences (Vol. 10652, p. 106520S). International
        Society for Optics and Photonics.
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Requires-Python: >=3.6
Description-Content-Type: text/markdown
