A starter repository to guide you through your earlier days of learning Datascience and Machine Learning!
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Starter Notebook · EDA Notebook · Links to Datasets

This project is a toolkit for a beginner in Data Science and Machine Learning. We will provide with guides for different aspects of Machine Learning like :

• Various types of Algorithms - Classification algorithms , Regression algorithms , Clusturing algorithms , Neural Networks , Deep learning.
• Exploratory Data Analysis [EDA].
• Advance Topics.

Along with all these guides , we will also provide resources from which beginners can learn and take help from. We will provide links to beginner friendly Datasets , and also gradually post links of Datasets which require higher expertise. This way one can become an expert from a beginner.

Most of our guides will be Jupyter Notebooks and python files with proper documentation. Other informations will be provided in Markdown files.

• Jupyter Notebook
• Python

Beginners !! First choose the discipline you want to learn and work on , then proceed with the steps:

• Download the appropriate dataset from the provided links. (Link to the Datasets)
• Take help from the Guiding Notebooks
• And build your own Dataset project !!

See the open issues for a list of Projects you can work on (and learn).

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated. Your contributions would help other beginners !!

1. Fork the Project
2. Create your Project Branch ( git checkout -b Project/MLAlgo )
3. Add your Changes ( git add . )
4. Commit your Changes ( git commit -m 'Add the Project' )
5. Push to the Branch ( git push origin Project/MLAlgo )
6. Open a Pull Request

Distributed under the MIT License. See LICENSE for more information.

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