https://github.com/samia35-2973/learning-data-science
📚 This repository is my personal data science learning hub. Explore my journey from the very basics to advanced techniques. Dive into Python, data manipulation, analysis, visualization, and machine learning. Join me as I learn, grow, and experiment in the world of data science.
https://github.com/samia35-2973/learning-data-science
advanced-machine-learning data-cleaning data-manupulation data-preprocessing data-science-roadmap data-science-tutorials data-structures-and-algorithms data-visualization deep-learning exploratory-data-analysis feature-engineering machine-learning mongodb natural-language-processing neural-network object-oriented-programming python r sql statistics
Last synced: 3 months ago
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📚 This repository is my personal data science learning hub. Explore my journey from the very basics to advanced techniques. Dive into Python, data manipulation, analysis, visualization, and machine learning. Join me as I learn, grow, and experiment in the world of data science.
- Host: GitHub
- URL: https://github.com/samia35-2973/learning-data-science
- Owner: Samia35-2973
- License: mit
- Created: 2023-08-28T12:46:46.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2023-09-08T09:24:56.000Z (about 2 years ago)
- Last Synced: 2023-09-08T10:34:32.202Z (about 2 years ago)
- Topics: advanced-machine-learning, data-cleaning, data-manupulation, data-preprocessing, data-science-roadmap, data-science-tutorials, data-structures-and-algorithms, data-visualization, deep-learning, exploratory-data-analysis, feature-engineering, machine-learning, mongodb, natural-language-processing, neural-network, object-oriented-programming, python, r, sql, statistics
- Language: Jupyter Notebook
- Homepage: https://github.com/Samia35-2973/Learning-Data-Science
- Size: 79.1 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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Welcome to my data science learning journey! This repository serves as a collection of my code, notes, and projects as I dive into the world of data science from scratch.
Table of Contents
- [About](#about)
- [Built With](#built-with)
- [Getting Started](#getting-started)
- [Usage](#usage)
- [Cloning](#cloning)
- [Step by Step Guide](#step-by-step-guide)
- [Support](#support)
- [Project assistance](#project-assistance)
- [Contributing](#contributing)
- [Authors & contributors](#authors--contributors)
- [Acknowledgements](#acknowledgements)
- [License](#license)
---
## About
In this repository, I'm documenting my learning process as I explore the various aspects of data science. From foundational concepts to advanced techniques, this journey is all about gaining a solid understanding of data manipulation, analysis, visualization, and machine learning.
### Built With
#### Languages
- Python
- R
#### Technologies
- Jupyter Notebook
## Getting Started
## Usage
### Cloning
Just clone if you need the copy in your device.
```
git clone https://github.com/Samia35-2973/Learning-Data-Science.git
```
### Step by step guide
Coming Soon!
## Support
Reach out to the maintainer at one of the following places:
- [GitHub issues](https://github.com/Samia35-2973/Learning-Data-Science/issues/new?assignees=&labels=question&template=04_SUPPORT_QUESTION.md&title=support%3A+)
- Contact options listed on [this GitHub profile](https://github.com/Samia35-2973)
## Project assistance
If you want to say **thank you** or/and support active development of Learning Data Science:
- Add a [GitHub Star](https://github.com/Samia35-2973/Learning-Data-Science) to the project.
- Tweet about the Learning Data Science.
- Write interesting articles about the project on [Dev.to](https://dev.to/), [Medium](https://medium.com/) or your personal blog.
Together, we can make Learning Data Science **better**!
## Contributing
First off, thanks for taking the time to contribute! Contributions are what make the open-source community such an amazing place to learn, inspire, and create. Any contributions you make will benefit everybody else and are **greatly appreciated**.
Thank you for being involved!
## Authors & contributors
The original setup of this repository is by [Samia Haque Tisha](https://github.com/Samia35-2973).
For a full list of all authors and contributors, see [the contributors page](https://github.com/Samia35-2973/Learning-Data-Science/contributors).
## Acknowledgments
I would like to express my heartfelt gratitude to the following individuals, courses, and resources that have played a pivotal role in my journey to learn data science:
- **Kaggle Courses**: I extend my sincere thanks to Kaggle for providing exceptional data science courses that have helped me build a strong foundation in this field.
- **YouTube Tutorials**:
- **Krish Naik**: Krish Naik's educational and insightful tutorials have been instrumental in deepening my understanding of various data science concepts.
- **Codebasics**: The tutorials from the Codebasics YouTube channel have been a valuable resource for practical data science knowledge.
- **freeCodeCamp**: freeCodeCamp's data science tutorials and community have been a constant source of inspiration and learning.
- **Websites**:
- **w3schools**: The w3schools website has been a go-to resource for expanding my knowledge of programming languages and web technologies, which are integral to data science.
- **AI like ChatGPT (OpenAI)**: AI models like ChatGPT have provided assistance and answers to numerous questions, making my learning journey more interactive and efficient.
- **Samia Haque Tisha**: Last but not least, I am proud of my own dedication and progress in the world of data science.
I am grateful for the wealth of knowledge, guidance, and support these resources have provided. They have been instrumental in helping me acquire the skills and knowledge necessary for a successful career in data science.
As I continue to learn and grow, I look forward to applying this knowledge in practical projects and contributing to the data science community.
Thank you to all the individuals and organizations that have made this journey possible.
## License
This project is licensed under the **MIT license**.
See [LICENSE](LICENSE) for more information.