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Data Science Projects

This repository contains various data science projects, each focusing on different aspects of machine learning and data analysis. Below is a brief overview of each notebook and how to get started.

Projects

1. Acidity Prediction

  • Description: Predicts acidity levels in wine based on various features using machine learning algorithms.
  • File: Acidity_Prediction.ipynb

2. California Housing Price Prediction

  • Description: Predicts housing prices in California using a dataset and regression models.
  • File: California_Housing_Price_Prediction.ipynb

3. Diabetes Prediction

  • Description: Predicts the likelihood of diabetes based on patient data using classification algorithms.
  • File: Diabetes_Prediction.ipynb

4. Digit Classification

  • Description: Classifies handwritten digits from the MNIST dataset using machine learning models.
  • File: Digit_Classification.ipynb

5. Instagram User Analytics

  • Description: Analyzes Instagram user data to gain insights into user behavior and engagement.
  • File: Instagram_User_Analytics.ipynb

6. Iris Classification

  • Description: Classifies iris flower species based on petal and sepal measurements using classification techniques.
  • File: Iris_Classification.ipynb

7. Named Entity Recognition (NER) with NLTK

  • Description: Performs Named Entity Recognition on text data using NLTK.
  • File: Named_Entity_Recognition_(NER)_with_NLTK.ipynb

8. Penguin Classification

  • Description: Classifies penguin species based on various features using machine learning algorithms.
  • File: Penguin_Classification.ipynb

9. Power Consumptions

  • Description: Analyzes power consumption data to identify trends and make predictions.
  • File: Power_Consumptions.ipynb

10. Titanic Survival Prediction

  • Description: Predicts survival chances of passengers on the Titanic using classification models.
  • File: Titanic.ipynb

11. Wine Quality Classification

  • Description: Classifies wine quality based on chemical properties using machine learning algorithms.
  • File: Wine_Quality_Classification.ipynb

12. Text Classification for News Articles

  • Description: Classifies news articles into different categories using text classification techniques.
  • File: text_classification_for_news_articles.ipynb

Getting Started

  1. Clone the Repository:

    git clone https://github.com/yourusername/repositoryname.git
  2. Navigate to the Project Directory:

       cd repositoryname
    
  3. **Install Required Packages: **

    You may need to install the necessary Python libraries.

    You can do this using pip:

       pip install -r requirements.txt
  4. Run a Jupyter Notebook:

    Start Jupyter Notebook and open the desired notebook file:

    jupyter notebook
    

License

This repository is licensed under the MIT License. See the LICENSE file for more information.

Contributing

If you would like to contribute to this repository, please open an issue or submit a pull request.

Contact

For any questions or feedback, please contact goutamhegde2000g@gmail.com.