Page 167 - Robotics and AI class 10
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• 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.
For example, if we want to prepare an AI model to predict the school average of students in board examination, we
will feed the marks obtained by students in board examination in the previous years, this will be treated as training
data. Once the model is ready, it will predict the school average for the coming year. Now when we are testing it,
we feed the different data set and that is the testing data.
Data Features
Data features refers to the type of data that you want to collect. In the above example, the data features would
be each subject average, number of students taking the exam, theory and practical marks distribution of each
subject, etc.
Data Sources
Data is the base for any AI project to be built. When the data is acquired, it's important to check if it's from a
reliable and authentic source for the accuracy of the project.
Also, the acquisition methods should be authentic so that there's no conflict in achieving project goals.
There are various sources to collect relevant data for our project:
• Surveys: Data can be collected from online surveys, telephonic surveys or in-person surveys and collect
responses. Surveys are a way of collecting data from a group of people in order to gain information and insights
into various topics of interest. The process involves asking people for information through questionnaires which
can be online or offline. It can be considered as a data source.
• Web Scraping: Data or information can also be extracted from a website. Web scraping or Data scraping is the
method of downloading information from the World Wide Web (WWW) and storing it onto your computer for
later reference. The data collected in this way is an online data.
• Sensors: Data can also be collected from various sensors like collecting environmental data and storing it in
some data storage solutions. Sensors are connected through gateways which enable them to collect live data
in the offline mode.
• Cameras: Data can be seen, written down or recorded onto the computer. Cameras are used to collect data in
the form of images. CCTV, web cameras, surveillance cameras are big sources of visual data that can be acquired
from various places.
• Observations: It is a method of collecting data by watching facts as they occur. Using the observation technique,
data can be analysed and used for testing the model.
• Application Programming Interface (APIs): APIs are a set of functions and procedures that allow one
application to connect to another. So, one of the ways of collecting data is through APIs that can be used to
collect data from social media services for analysis.
There are times using the internet, we acquire unauthentic data from websites for our AI project. Extracting private
data can be an offence. So, keeping this in mind we should ensure the data is collected from open-sourced
websites hosted by the government. They are one of the most reliable and authentic sources of information.
These portals have information collected in suitable format that can be downloaded. Some of the open-sourced
government portals are data.gov.in, india.gov.in, etc.
After discussing the data, let's understand the concept of system maps.
Components of AI Project Framework 165

