What's included

• Project Plan and Timeline

  Detailed project roadmap with milestones and deadlines.

• Requirements Documentation

  Functional and non-functional requirements. User stories and acceptance criteria.

• Data Collection and Preparation

  Data acquisition plan. Raw data sets. Data cleaning and preprocessing scripts. Exploratory data analysis (EDA) report.

• Model Development

  Jupyter notebooks or scripts for model training. Description of model architecture and algorithms used. Hyperparameter tuning details. Model training logs and metrics.

• Model Evaluation

  Evaluation metrics and performance reports (e.g., accuracy, precision, recall).

• Model Documentation

  Detailed description of the final model. Assumptions and limitations. Guidelines for model retraining and updates.

• Integration

  API endpoints for model inference. Integration with existing systems and applications. Load testing and performance optimization reports.

• Documentation

  Code documentation (comments, readme files). API documentation (Swagger, Postman collections). User manuals and guides for using the model and API.

• Final Delivery and Handover:

  Complete source code repository. Access credentials for all services and environments. Final project report and summary. Post-deployment support plan.