What's included

• Project Proposal

  A detailed proposal outlining the scope, objectives, methodologies, and timelines of the AI/ML project.

• Reworked Data / Cleaned

  Collecting and preprocessing relevant data required for training the AI/ML models. This may include data cleaning, feature engineering, and data augmentation.

• MVP for the Model

  Building and training AI/ML models tailored to the client's specific needs. This involves selecting appropriate algorithms, fine-tuning model parameters, and optimizing performance.

• Documentation

  Documentation: Providing comprehensive documentation, including technical specifications, architecture diagrams, and explanations of the AI/ML models, algorithms, and methodologies used. This ensures transparency and ease of understanding for future reference.

• Code Repository

  Sharing a code repository containing the source code for the developed AI/ML models and any supporting scripts or tools used during the project.

• The Model

  Everything the clients may need to run the project with no problems.

• Ongoing Support

  Offering post-deployment support, such as bug fixing, model updates, and addressing any issues that may arise during the implementation or operational phases.