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https://github.com/jhwach/pycamp
https://github.com/jhwach/pycamp
javascript machine machine-learning machine-learning-algorithms numpy numpy-arrays numpy-library numpy-neural-network pandas pandas-dataframe pandas-library pandas-python pandas-tutorial
Last synced: 13 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/jhwach/pycamp
- Owner: Jhwach
- License: apache-2.0
- Created: 2024-01-29T10:09:21.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-01-30T05:32:46.000Z (about 1 year ago)
- Last Synced: 2024-11-18T23:20:02.879Z (3 months ago)
- Topics: javascript, machine, machine-learning, machine-learning-algorithms, numpy, numpy-arrays, numpy-library, numpy-neural-network, pandas, pandas-dataframe, pandas-library, pandas-python, pandas-tutorial
- Language: Jupyter Notebook
- Homepage: https://ascendantaditya.github.io/Pycamp/
- Size: 85 KB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# PyCamp Workshop
Welcome to PyCamp, a workshop where we explore Python, Data Science libraries, and various coding exercises. This repository contains code and resources from the workshop.
## Table of Contents
- [Introduction](#introduction)
- [Installation](#installation)
- [Workshop Content](#workshop-content)
- [How to Use the Code](#how-to-use-the-code)
- [Dependencies](#dependencies)
- [Contributing](#contributing)
- [License](#license)
## Introduction
PyCamp is a hands-on workshop designed to introduce participants to Python and essential Data Science libraries. Throughout this workshop, we cover topics such as Python basics, data manipulation with Pandas, data visualization with Matplotlib and Seaborn, web development with Flask and Django, and machine learning with TensorFlow.
## Installation
To get started, it's recommended to set up a virtual environment and install the necessary dependencies. Follow the steps below:
1. Clone this repository:
```bash
git clone https://github.com/ascendantaditya/Pycamp.git
cd Pycamp
```
2. Create a virtual environment:
```bash
python -m venv .venv
```
3. Activate the virtual environment:
- On Windows:
```bash
.\venv\Scripts\activate
```
- On Unix or MacOS:
```bash
source venv/bin/activate
```
4. Install dependencies using pip:
```bash
pip install -r requirements.txt
```
## Workshop Content
This repository includes code and examples for the following topics:
- Python Basics
- Data Manipulation with Pandas
- Data Visualization with Matplotlib and Seaborn
- Web Development with Flask and Django
- Machine Learning with TensorFlow
Feel free to explore the directories to access the specific content related to each topic.
## How to Use the Code
Each topic has its dedicated folder containing code examples and exercises. Follow the instructions provided in each directory to understand and run the code. You can also use the code as a reference for your projects or further exploration.
## Dependencies
The workshop code relies on the following Python libraries:
- [NumPy](https://numpy.org/)
- [Matplotlib](https://matplotlib.org/)
- [Pandas](https://pandas.pydata.org/)
- [Seaborn](https://seaborn.pydata.org/)
- [Flask](https://flask.palletsprojects.com/)
- [Django](https://www.djangoproject.com/)
- [TensorFlow](https://www.tensorflow.org/)
Make sure to install these dependencies in your virtual environment as described in the [Installation](#installation) section.
## Contributing
If you find any issues, have suggestions, or want to contribute to this workshop, feel free to open an [issue](https://github.com/your_username/Pycamp/issues) or submit a [pull request](https://github.com/ascendantaditya/Pycamp/pulls).
## License
This workshop material is licensed under the [MIT License](LICENSE). Feel free to use, share, and modify as needed.