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4.  How can a machine become intelligent?
                Ans.  Artificial Intelligence makes the machines intelligent. Programming along with some aspects of human intelligence
                    like decision-making and problem-solving gives rise to intelligent machines. Machines are fed with enough data and
                    correct algorithms to make them intelligent.
                  5.  “The more the data, the better will be the analysis” Justify.
                Ans.  AI requires large  amounts of data to find  the  latest trends and  patterns. For  example,  I plan  to organise a  social
                    gathering in an open air setup in the month of August in Delhi. I will have to look for a weather forecast for the same
                    and also look at the previous years' trends. So data collection is the base for analyses and pattern recognition models.
                    From  those patterns, predictive models  can be made. Applications of AI in data sciences  can be seen in weather
                    forecasting, score prediction, targeted advertisement, predictive analysis in finance.
                  6.  Explain the ethical issue related to problem selection.

                Ans.  When identifying an issue for an AI project, consider how it will influence individuals as well as society. These are some
                    important ethical issues:
                    •  Fairness: Make sure that the AI system does not unfairly favour a particular group above others.
                    •  Privacy: Ensure that the AI system protects the confidentiality of individuals and never collects or uses the private
                      data of individuals without their consent.
                    •  Transparency: People should know how exactly the AI system functions as well as why specific choices are made.
                    •  Social impact: Examine how the AI system may influence society as a whole, and how it might encourage biases or
                      cause of social divisions.
                    •  Environmental impact: Examine how AI systems could have negative impacts on the environment. For example,
                      consuming a lot of electricity or emitting pollutants.
                  7.  What is Data? Also, explain the types of data.

                Ans.  Data is a piece of raw information or facts and statistics collected together for reference or analysis. They are raw facts
                    that need to be processed to get meaningful information. Whenever we want the AI project to be able to predict an
                    output, we need to train it with a data set first. Data plays an important part of an AI project as it creates the base on
                    which the AI project is built.

                     There are two types of data:
                    •  Training data: It is data on which we train our AI project model. It is basically to fit the parameters of the project for
                      the model. In training data, the output is available to the model.
                    •  Testing data: It is used to check the performance of an AI model. In testing data, the data is not seen for which the
                      predictions have to be made.
                  8.  What is the need for visualising data?

                Ans.  The needs for data visualisation are:
                    •  It simplifies the complex quantitative information.
                    •  It analyses and explores big data easily.
                    •  It identifies the areas for improvement.
                    •  It identifies the relationship between data points and variables.
                    •  It explores new patterns and reveals hidden patterns.

                  9.  What is the application of AI in healthcare?
                Ans.  For saving human lives, the medical industry is relying on AI on many fronts. Healthcare organisations are using IBM
                    Watson for medical diagnosis. Google’s DeepMind has successfully developed a system that can analyse retinal scans
                    and spot symptoms of sight-threatening eye diseases. AI is used in diagnostic centres to analyse samples of tissues and
                    provide accurate results.




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