Rationalizing the Use of a Neural Network

Requirements Clarification & Assessment

1. Understanding the Business Problem

   • Clarify Objectives: Begin by clarifying the exact nature of the business challenge. Is it a classification, regression, or clustering problem? What are the key performance indicators (KPIs) or metrics of success?
   • Stakeholder Needs: Identify the level of understanding among stakeholders regarding AI and neural networks. Determine their expectations for model interpretability and explainability.
   • Data Availability: Assess the availability and quality of data. Do we have a cleaned, labeled dataset? What is the size and complexity of the dataset?

2. Evaluating the Need for a Neural Network

   • Complexity of the Problem: Determine if the problem involves complex patterns, large-scale data, or unstructured data (e.g., images, text, audio) where NNs excel.
   • Prior Attempts: Have simpler models been tried, and if so, why were they insufficient? This helps justify the need for a more complex model.

3. Resource Assessment

   • Infrastructure: Evaluate if the current infrastructure can support the computational demands of training and deploying a neural network.
   • Timeline and Budget: Consider the timeline for project completion and budget constraints. Are there resources for ongoing maintenance and updates?