semvec/pypi-packages huggingface dataset:
mlba 2.0.2
Utility functions for 'Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python' (2nd edition)

[![PyPI](https://badge.fury.io/py/mlba.svg)](https://pypi.org/project/mlba/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/mlba)](https://pypi.org/project/mlba/)
![Python](https://github.com/gedeck/mlba-python/actions/workflows/build.yml/badge.svg)

# Machine Learning for Business Analytics: Concepts, Techniques, and  Applications in Python

Collection of utility functions used in the book

> _Machine Mining for Business Analytics: Concepts, Techniques, and Applications in Python_ (Second Edition) 
> Galit Shmueli, Peter C. Bruce, Peter Gedeck, and Nitin R. Patel
> (c) 2025 John Wiley & Sons, Inc. 

Code for the book and the used datasets are available on https://www.dataminingbook.com/book/python-edition.


## Installation
Use `pip` to install the `mlba` package from pypi (https://pypi.org/project/mlba/).
```
pip install mlba
```
Should this not work, for example when you are behind a firewall, download the package from pypi and install from file, e.g.
```
pip install mlba-2.0.tar.gz 
```
prebuilt-hnsw 0.8.1
Prebuilt wheels for hnswlib
Requires Python: >=3.10

# hnswlib-prebuilt

Prebuilt wheels for [hnswlib](https://github.com/nmslib/hnswlib).

Originally created by Yury Malkov and the hnswlib contributors: https://github.com/nmslib/hnswlib

This package provides precompiled binaries for easy installation on:
- Linux (x86_64, aarch64)
- macOS (x86_64, arm64)
- Windows (x86_64) 

Supports Python 3.10+

Apache License 2.0
simple-flagger-private 1.0
A simple package for a flag parsing
Requires Python: >=3.10

# Flag library
Simple flag processing for Python

### Supported types:
    
- [x] int
- [x] float
- [x] str
- [x] bool
- [x] list

## Installation

```bash
pip install simple-flagger
```

## Simple usage example
```python
# python example.py -f 10.3
from flagger import Flagger

if __name__ == "__main__":
    flag = Flagger()
    f_flag = flag.parse_flag("-f", float)

    print(f_flag) # >> 10.3
```

## List usage example
```python
# python example.py -l 1,2,3
from flagger import Flagger

if __name__ == "__main__":
    flag = Flagger()
    l_flag = flag.parse_flag("-l", list, sep=",")

    print(l_flag) # >> ['1', '2', '3']
```

TODO
- finding tags existence only, not value
- creating list of allowed tags