What's included

• Report on Data Analysis:

  Detailed observations and conclusions derived from the examination of the given datasets.

• Predictive Models:

  Machine learning models created for a range of applications, such as clustering, regression, and classification.

• Data visualisations:

  Using programmes like Matplotlib, Seaborn, or Tableau, one may create visual representations of data patterns and insights.

• Model Evaluation:

  Model evaluation includes performance analysis and evaluation measures for the created prediction models.

• Documentation:

  Detailed documentation that addresses the stages involved in preparing data, developing models, and interpreting the outcomes.

• Recommendations:

  Actionable suggestions derived from insights gained from the model and data analysis.

• Codebase:

  Clear, well-documented codebase for future reference and repeatability.

• Presentation:

  A succinct presentation outlining methodology, important discoveries, and stakeholder suggestions.

• Deployment Plan & Support and Maintenance Plan:

  A strategy for introducing models into operational settings, if relevant. Detailed instructions for continuing to provide support and upkeep for deployed models.