Page 237 - AI Ver 1.0 Class 9
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7.  What is the need of visualising data?
              Ans.  The need for data visualisation are:
                     • Simplifies the complex quantitative information.
                     • Analyse and explore big data easily.
                     • Identifies the areas for improvement.
               8.  What is a bar chart? Give its uses.
              Ans.  Bar charts are graphs that represent categorical data with rectangular bars with heights and length proportional to the
                  values that they represent. It is used to compare things between different groups or to track changes over time. For
                  example, marks of 5 subjects to compare, rise in population in five years, changing fuel price every month.
               9.  What is Data Modelling?
              Ans.  Data Modelling is defined as the process of designing  decision-making algorithms that has to be trained on a set of
                  data (which was acquired at the Data Acquisition stage for the problem you scoped in the Problem Scoping stage) and
                  apply that learning to recognise certain types of patterns.
               10.  What is deep learning? Give examples.
              Ans.  Machines can draw meaningful inferences from large volumes of datasets. In deep learning, the machine is trained with
                  a huge amount of data which helps it train itself. Deep learning is a machine learning algorithm that is inspired by the
                  functionality of our brain cells called neurons. For example, Google translate, image recognition in social media apps.
               11.  What is AI Project Deployment?
              Ans.  Deployment is the process of integrating a newly created AI model into an existing production environment to make
                  practical implementation of the model with actual data taken as input to give the desired output. It requires certain
                  settings to be done in terms of hardware and software so that the AI model can be put to use efficiently by the end users.
            C.  Competency-based/Application-based questions:

               1.  Scenario: The world of Artificial Intelligence revolves around Data. Every company, whether small or big, is mining data
                  from as many sources as possible. More than 70% of the data collected till now has been collected in the last 3 years
                  which shows how important data has become in recent times. It is not wrongly said that Data is the new gold. This
                  makes us think. Answer the following questions:
                  a.  Define data.
                  b.  Under which step of the AI Project Cycle does data collection come?
                  c.  Where are the various ways of collecting data?
                  d.  Name the reliable websites to collect data.
                  e.  “It is not wrongly said that Data is the new gold.” Justify.
              Ans.  a.   Data can be a piece of information or facts and statistics collected together for reference or analysis. Whenever we
                     want an AI project to be able to predict an output, we need to train it first using data.
                  b.  Data Collection is Step 2 of AI Project Cycle.
                  c.  The following are the various ways of collecting data:
                     ●  Surveys
                     ●  Web Scraping
                     ●  Sensors
                     ●  Cameras
                     ●  Observations
                     ●  Application Program Interface
                  d.  Some of the open-sourced Govt. portals are: data.gov.in, india.gov.in
                  e.   In today's information-driven economy, data is extremely valuable to just about any industry and profession, and
                     risk management is no exception. Businesses that are able to properly harness data can apply it to improve their
                     operations and make more efficient use of resources.

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