https://github.com/goutamhegde002/ml-and-data-science-projects
Few simple ML and Data Science related Projects
https://github.com/goutamhegde002/ml-and-data-science-projects
acidity-prediction data-science data-science-examples diabetes-prediction digit-classification housing-price-prediction instagram-analytics iris-classification jupyter-no machine-learning machine-learning-algorithms named-entity-recognition ner penguin-classification power-consumption-analysis predictive-analysis python-projects text-classification titanic-survival-prediction wine-quality
Last synced: 8 months ago
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Few simple ML and Data Science related Projects
- Host: GitHub
- URL: https://github.com/goutamhegde002/ml-and-data-science-projects
- Owner: goutamhegde002
- License: mit
- Created: 2024-08-27T06:16:01.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2024-08-27T08:52:12.000Z (about 1 year ago)
- Last Synced: 2025-01-08T19:18:51.688Z (9 months ago)
- Topics: acidity-prediction, data-science, data-science-examples, diabetes-prediction, digit-classification, housing-price-prediction, instagram-analytics, iris-classification, jupyter-no, machine-learning, machine-learning-algorithms, named-entity-recognition, ner, penguin-classification, power-consumption-analysis, predictive-analysis, python-projects, text-classification, titanic-survival-prediction, wine-quality
- Language: Jupyter Notebook
- Homepage:
- Size: 1.53 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 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**:
```bash
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:
``` bash
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.