In this document, based on the available project outline and summary of the project pitch, to the best of your abilities, you will come up with the technical plan or goals for implementing the project such that it best meets the stakeholder requirements.
A. Provide a solution in terms of human actions to confirm if the task is within the scope of automation through AI.
To assist in outlining the steps needed to achieve our final goal, outline the AI-less process that we are trying to automate with Machine Learning. Provide as much detail as possible.
In as direct terms as possible, provide the “Data Science” or "Machine Learning" problem statement version of the overview. Think of this as translating the above into a more technical definition to execute on. eg: a classification problem to segregate users into one of three groups on based on the historical user data available from a publicly available database
Provide a bulleted list to the best of your current understanding, of the concrete techinal goals and artifacts that, when complete, define the completion of the project. This checklist will likely evolve as your project progresses.
- Deliverable 1
- Deliverable 2
Data Science Projects should have an operationalized end point in mind from the onset. Briefly describe how you see the tool produced by this project being used by the end user beyond a jupyter notebook or proof of concept. If possible, be specific and call out the relevant technologies that will be useful when making this available to the stakeholders as a final deliverable.
Keep track of ongoing meetings in the Project Description document prepared by Spark staff for your project.
Note: Once this markdown is finalized and merge, the contents of this should also be appended to the Project Description document.