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• Arrows are used to represent relationships/interconnections.
                    • The ‘+’ and ‘-’ signs are indicators of the nature of a relationship. The arrowhead depicts the direction of the
                   effect and the sign (+ or -) shows their relationship.
                    • If the arrow goes from X to Y with a + sign, it means that both are directly related to each other. That means if
                   X increases, Y also increases and vice versa.
                    • If the arrow goes from X to Y with a -sign, it means that both elements are inversely related to each other. That
                   means if X increases, Y would decrease and vice versa.


                                 Task                                                #Experiential Learning



                     Visit the following link: https://ncase.me/loopy/

                     and create a System Map for how much quantity of food to be prepared every day in a
                     restaurant. Training data is to be taken as quantity consume for past 20 days and testing data
                     will be the quantity for next 10 days.




                         Data Exploration

                 After collecting accurate data, the next step is data exploration. Data exploration means finding the patterns
                 and trends in the data. It is the third stage in the AI project cycle and the initial step in data analysis. It is used to
                 understand what is in a dataset and the characteristics of the data.

                 Data exploration cleans the big data to provide an input to an AI project. Terabytes of data sitting in the data centre
                 unused is a burden, if correctly processed it can become digital gold.


                                 Task                                                #Experiential Learning



                     Activity: Data and Analysis

                     In reference to Case Study: Cleaning Ocean, observe the 4Ws problem canvas and Problem Statement
                     Template and answer the following questions:

                        • What are the data features needed?
                        • How will the features collected affect the problem?
                        • Where can you get the data?
                        • How frequent do you have to collect the data?
                        • What happens if you don’t have enough data?

                        • What kind of analysis needs to be done?
                        • How will it be validated?
                        • How does the analysis inform the action?
                     Also, perform the following tasks:
                        • Provide the brainstorming solutions for the problem statement.

                        • Identifying the possible data features affecting the problem.
                        • Creating system maps considering data features identified.


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