dmkarthiksrini / distributed_data_analysis

The goal of the project is to gain understanding and value from analysing disparate data sets. We will put into practise a number of different analytic methods, techniques, and algorithms, assess their performance, and then compare them to one another. Teamwork and regular meetings will aid in the planning and execution of the data analysis.

Distributed_Data_Analysis

This project is based on the course work for Distributed Data Analyses CS5811 at Brunel University London, for the Master program in Data Science & Analystics

Table of Contents

1. About the project

2. Contributing

3. License

4. Contributors

5. About the project

This project lies in the field of finance notable retail banking, and the main objective is to optimize credit allocation through the use of machine learning algorithms by classifying people into credit score brackets through based on their bank details and credit-related information.

2. Contributing

   1. Fork/Clone the Project
   2. Create your Feature Branch (git checkout -b phase/AmazingMilestone)
   3. Commit your Changes (git commit -m 'Complete data cleaning in Phase1 of data desciption and research question')
   4. Push to your Branch (git push origin feature/AmazingFeature)
   5. Notify other members about the changes (so others can pull in the latest)
   6. Open a Pull Request

3. License Distributed under the MIT License.

4. Contributors

   • https://github.com/dmkarthiksrini
   • https://github.com/palaciosma
   • https://github.com/amaboh
   • https://github.com/tanvimathur11
   • https://github.com/nehalgajraj

distributed_data_analysis's Issues

Research Question Identification

test

Dataset Selection

Identify the Dataset that we are focusing on for the Project.

Data Selection