This repository contains multiple machine learning case studies, each located in its respective directory. The case studies include various data preprocessing, analysis, and modeling steps. Below is a summary of the included case studies and their contents.
This project aims to provide a personalized cancer diagnosis using machine learning techniques.
PersonalizedCancerDiagnosis.ipynb: The main notebook containing the code and analysis.README.md: This file contains the documentation for the project.Personalized_Cancer Diagnosis/: Directory containing additional resources and files for the project.
This project focuses on analyzing and predicting duplicate questions on Quora using various machine learning models.
1.Quora.ipynb: Initial exploration and visualization of the Quora dataset.2.Quora_Preprocessing.ipynb: Data preprocessing steps including cleaning and feature engineering.3.Q_Mean_W2V.ipynb: Analysis and modeling using Mean Word2Vec embeddings.4.ML_models.ipynb: Implementation of various machine learning models for predicting duplicate questions.README.md: Documentation for the Quora Pair Plot project.
To run the notebooks, you need to have the following installed:
- Python 3.x
- Jupyter Notebook
- Required Python libraries (listed in the respective notebooks)
- Clone the repository:
git clone https://github.com/SaiNikhil02/ML-Case-Studies.git cd ML-Case-Studies ```sh
pip install -r requirements.txt
Navigate to the desired case study directory. Open the Jupyter Notebook: Select the notebook you want to run from the Jupyter interface.
Contributions are welcome! Please open an issue or submit a pull request for any improvements or bug fixes.
This project is licensed under the MIT License. See the LICENSE file for details.
Quora for providing the dataset used in the Quora Pair Plot project. Various open-source libraries used in the projects.