semvec/pypi-packages huggingface dataset:
pydigit 0.1.7
Hand Writing Digits Recognition program is an open-source python machine learning algorithm program. That program recognizes and predicts handwriting digits. PyDigit is an open-source and free to use python package
License: MIT
Keywords: Python MachineLearning

# Hand Writing Digits Recognition

Hand Writing Digits Recognition program is an open-source python machine learning algorithm program.
That program recognizes and predicts handwriting digits.

This project prepared to recognize and predict the handwriting digits both using Deep Learning and Machine Learning algortihms together.

In order, you have to install additional packages to work with this repository :

```
pip install tensorflow
```

```
pip install opencv-python
```

```
pip install numpy
```

```
pip install matplotlib
```

## Installation

Use the package manager to install digitreg.

```
pip install pydigit
```

## Index and Usage

This python project includes three of python files:
***
pydigit.success():
Includes main.py that shows the algorithm stats.
That stats are : How successfull and How many loss points algorithm have ?
***
pydigit.random(): 
Includes python file that is a handwriting digit predicter. 
That predicter picks random handwiritng digits from MINST algorithm and predicts both.
***
pydigit.recognize():
Includes python file that is a handwriting digit predicter. 
First of all you have to add a 28x28 image to your dir which python file you are working in that.
After that, give the image name as a parameter to the recognize() function. 
Finally let the program predicts your own handwriting digits.
***

## License

MIT Licence Included.

## Maintainer

Emir Yaman

Change Log
==========

0.0.1 (04/02/2021)
------------------
- First Release
LASER 0.0.5
A toolkit for large scale distributed training
License: MIT
Requires Python: >=3.6
Keywords: Distributed deep learning

# LASER (a toolkit for Large scAle diStributEd tRaining)
A toolkit for large scale distributed training

With LARSER we succeeded to train [DeBERTa 1.5B](https://github.com/microsoft/DeBERTa) model without model parallelism. The **DeBERTa 1.5B** model is the SOAT model on [GLUE](https://gluebenchmark.com/leaderboard) and [SuperGLUE](https://super.gluebenchmark.com/leaderboard) leaderboard. And it's the first model that surpass **T5 11B model** and human performance on SuperGLUE leaderboard. 

# TODOs
- [ ] Add documentation and usage examples

 git version: 57143200814583410acdd0c5ac0a0f8bab8a1f7e
 date: 2021-02-04 09:55:12.622124
digitreg 0.0.1
Hand Writing Digits Recognition program is an open-source python machine learning algorithm program. That program recognizes and predicts handwriting digits.
License: MIT
Keywords: Machine Learning

# Hand Writing Digits Recognition

Hand Writing Digits Recognition program is an open-source python machine learning algorithm program.
That program recognizes and predicts handwriting digits.

This project prepared to recognize and predict the handwriting digits both using Deep Learning and Machine Learning algortihms together.

In order, you have to install additional packages to work with this repository :
```bash
pip install tensorflow
```

```bash
pip install opencv-python
```

```bash
pip install matplotlib
```

```bash
pip install matplotlib
```

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install digitreg.

```bash
pip install digitreg
```

## Index and Usage

This python project includes three of python files:
***
digitreg.success():
Includes main.py that shows the algorithm stats.
That stats are : How successfull and How many loss points algorithm have ?
***
digitreg.random(): 
Includes python file that is a handwriting digit predicter. 
That predicter picks random handwiritng digits from MINST algorithm and predicts both.
***
digitreg.recognize():
Includes python file that is a handwriting digit predicter. 
First of all you have to add a 28x28 image to your dir which python file you are working in that.
After that, give the image name as a parameter to the recognize() function. 
Finally let the program predicts your own handwriting digits.
***

## License

MIT Licence Included.

## Maintainer
Emir YarkÄ±n Yaman
[GitHub](https://github.com/Weinoose)
[PyPi](https://pypi.org/user/Weinoose/)

Change Log
==========

0.0.1 (04/02/2021)
------------------
- First Release
dirEx 0.0.6
An extension to the built-in function dir()
License: MIT
Keywords: dir extend built-in

# DirEx
> An extension to the built-in function dir() for Python  


## APIs
- show_dir_info
- show_dir_method
- show_dir_module


## Install
`pip install direx`


## Example
```Python
from direx import show_dir_info, show_dir_method, show_dir_module

import os

show_dir_module(os)
show_dir_method(os)
show_dir_info()
```
AiDragonfly 1.1.9
AiDragonfly 是爱其科技推出的python编程包，和ONEBOT主控、智能积木主控深度融合，和手机端拖块编程 Dragonfly 一脉相承.
License: MIT
Keywords: AiDragonfly 是支持ONEBOT主控的python编程包

ONEBOT教育机器人 是小米生态链企业爱其科技 推出的一款面向 教育、创客 的编程机器人。同时提供模块化图形编程 和 Python编程。模块化图形编程 面向中小学生可视化编程，Python面向高中生、大学生、创客教育等。
Python是一种解释型、面向对象、动态数据类型的高级程序设计语言，具有卓越的通用性、高效性、平台移植性和安全性。近几年 Python 在数据挖掘、人工智能等领域较为流行。
AiDragonfly 是爱其科技推出的python编程包，支持Python 3.0 及以上。
和ONEBOT主控、智能积木主控深度融合，和手机端拖块编程 Dragonfly 一脉相承。
推荐采用流行的集成开发环境PyCharm Community Edition进行python程序开发。
基于集成开发环境PyCharm Community Edition 的安装、使用 参见附录二 Python集成开发环境的安装。
nestall 0.1.1
Nest is a collection of tools.
License: MIT
Requires Python: >=3.6,<4.0

# NEST

nest is a collection of tools. In particular, is a series of small command line tool.

now, it supported tools as:

- [x] `nest w`: Current location weather
- [x] `nest t`: Language translation
- [x] `nest b`: Bytes convert

### install
for install, just use pip:
```
pip install nestall
```
Then, execute on the command line:
```
nest --help
```

### tools
- `nest t`
    **nest t** provide translation service between diffrent languages, you just need to type `nest t <query>` at the command line, like this:


    ```
    > nest t hello
    ---------------------
    你好
    ---------------------
    ```

    type `nest t --help` for more feature！

- `nest w`
    provide weather report, just type `nest w <location>`：
    ```
    > nest w beijing
    beijing: ☀️ +9°C
    ```
- `nest b`
    provide betes and MB and GB covert to each other:
    ```
    > nest b 1024
    bytes: 1024, MB: 1.00, GB: 0.00
    > nest b -m 1024
    bytes: 1048576, MB: 1024.00, GB: 1.00
    > nest b -g 1
    bytes: 1048576, MB: 1024.00, GB: 1.00
    ```