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Stage 5   Evaluation

              The testing phase of the AI project cycle is a critical step where the model's performance is evaluated to ensure it
              meets the predefined goals and requirements. If the model does not fulfil the required objectives, modifications
              may be necessary. Once  the  developer  ensures  the  model achieves satisfactory  results  and aligns  with the
              project's goals, the AI project proceeds to the deployment phase. This means the project will be transitioned
              into an operational state, where it is fully implemented and handed over to the end-user for practical use.


               Stage 6   Deployment

              In  this  phase,  the  best-performing  model  is  seamlessly  integrated  into  the  production  environment.  This
              integration  involves  implementing  the  model  in  a  real-world  setting  where  it  can  be  used  for  practical
              applications. Additionally, this stage requires setting up a system for continuous monitoring to ensure that the
              model consistently delivers accurate and reliable results over time. Ongoing maintenance is also established
              to  address  any  potential  issues  that  might  arise,  such  as  changes  in  the  data,  evolving  requirements,  or
              performance degradation. The goal is to sustain the model's effectiveness, adapting as needed to maintain
              optimal performance and ensure that the solution remains valuable and efficient throughout its lifecycle.

                              Reboot


                    1.  Name and explain the 4Ws in problem scoping stage of AI project cycle.






                    2.  Which visual tools will you use to transform the raw data into a visual format?









              Consider a given scenario to understand the AI project cycle
              A High School aims to enhance its waste management practices by encouraging students and staff to recycle
              correctly. However, many people accidentally put waste into the wrong bins, which contaminates recyclable
              materials and increases waste sent to landfills. To address this challenge, the school decides to develop an
              AI-powered system capable of automatically identifying and sorting waste, thereby improving recycling efficiency
              and reducing environmental impact.
              The different stages of the AI project cycle for the given problem are as follows:

               Stage 1   Problem Scoping
              The goal of this stage is to define the problem and outline its objectives.
                 • Goal: Address the problem of incorrect waste disposal, which leads to ineffective recycling efforts at the school.
                 The  objective  is  to  create  a  system  that  can  identify  different  types  of  waste  and  sort  them  correctly  into
                 recycling, compost, or trash bins.

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