semvec/pypi-packages huggingface dataset:
tinynn-py 1.0.2
A tiny neural network library.

# Tinynn

Tinynn is a lightweight neural network library built entirely in NumPy, designed to help developers understand the nitty-gritty details of neural networks. With its clean and concise code, Tinynn offers a great learning platform for those who want to deepen their understanding of the inner workings of neural networks.

Despite its simplicity, Tinynn has all the key features of a neural network library, including support for feedforward and recurrent networks, various activation functions, and common optimization algorithms. Whether you're a student, researcher, or machine learning enthusiast, Tinynn is an excellent tool for experimenting with neural network architectures and training algorithms.

## Key Features

- Lightweight and easy-to-understand implementation
- Support for feedforward and recurrent networks
- Various activation functions to choose from
- Common optimization algorithms
- Built entirely in NumPy for efficient numerical computations

## Installation

To install Tinynn, you can use pip:

```bash
pip install tinynn-py
```

## Usage
Here's a basic example demonstrating how to create a feedforward neural network using Tinynn:

```python
from tinynn.models import Sequential
from tinynn.layers import Dense
import numpy as np

model = Sequential()

X = np.array([[1,2,3],
     [5,4,3],
     [2,3,4]])
y = np.array([0, 0, 1])

model.add(Dense(3,64))
model.add(Dense(64,2,activation='softmax'))

model.compile_model(learning_rate=0.01, optimizer='adagrad') #Also available params: decay_rate,momentum(only for sgd) and optimizer = sgd,adagrad
model.fit(X,y,epochs=1000)
```

## Contributions
Contributions to Tinynn are welcome! Whether you want to report a bug, suggest a new feature, or submit a pull request, please feel free to do so. Let's make Tinynn better together.

## License
Tinynn is released under the MIT License. See the LICENSE file for more details.
archbuilder 0.1.2
A tool to enable developers set up their projects quickly
Requires Python: >=3.7


# Archbuilder

Archbuilder is a tool that aims to speed up the setting up of projects by creating the project directories and files from user-defined templates.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install Archbuilder.
```bash
  pip install archbuilder
```
    
## Usage

##### 1. By using a python script
```python
# Import archbuilder
from builder import Builder
from template import Template

# Create a template from a json file
template = Template('sass.json')

# Create the project tree from the template
project = Builder('sass', template)
project.build()
```

##### 2. By using the command-line
Invoke archbuilder to create your project. Pass the name of the project as the first argument and the path to the json file as the second argument
```bash
archbuilder sass sass.json
```

## Contributing

Contributions are always welcome!

For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.
## License

[![MIT License](https://img.shields.io/badge/License-MIT-green.svg)](https://choosealicense.com/licenses/mit/)
TicTacToeAI 0.0.4
Tic Tac Toe with AI.
Requires Python: >=3.6
Keywords: MinMax,Diffcult,AI

# Tic Tac Toe with AI
[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)   

## Discription
This is a simple command-line implementation of the Tic Tac Toe game in Python, where you can play against an AI opponent. The AI opponent uses the minimax algorithm to make its moves, providing a challenging gameplay experience.

## Usage

- Make sure you have Python installed in your system.
- Run Following command in the Terminal.
 ```
  pip install TicTacToeAI
  ```
## Example

 ```
# test.py
import TicTacToeAI

## To run

# For easy level of game.
run = TicTacToeAI.play_game() 

# For medium level of game.
run = TicTacToeAI.play_game('medium')

# For hard level of game.
run = TicTacToeAI.play_game('hard')

```

## Run the following Script.
 ```
  python test.py
 ```

## Note 
- I have tried to implement all the functionality, it might have some bugs also. Ignore that or please try to solve that bug.