Page 181 - Robotics and AI class 10
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4. Stakeholders are the people who face problem scoping. ……….……
5. Problem Statement Template helps us to summarise all the key points into one single
Template for future reference. ……….……
SECTION B (Subjective Type Questions)
A. Short answer type questions:
1. Name all the stages of an AI Project cycle.
Ans. Problem Scoping, Data Acquisition, Data Exploration, Modeling and Evaluation.
2. What is a problem statement template and what is its significance?
Ans. Problem Statement Template helps us to summarise all the key points into one single Template so that in future,
whenever there is a need to look back at the basis of the problem, we can take a look at the Problem Statement
Template and understand the key elements of it.
3. What precautions to be taken while acquiring data for developing an AI Project?
Ans. Data should be collected from an authentic source, and should be accurate. The redundant and irrelevant data should
not be a part of prediction.
4. Explain Data Exploration stage.
Ans. This is the third stage in the AI project cycle. It refers to exploring the large data to uncover the patterns or trends
needed for the AI project. It is considered to be the first step in data analysis where unstructured data is explored,
researched, filtered and visualised to decide the strategy for the type of model used in the later stage.
B. Long answer type questions:
1. What are sustainable development goals?
Ans. When we cannot observe a problem around us then we should refer to the 17 goals that have been announced by the
United Nations as the Sustainable Development Goals. These goals are to be achieved by 2030 as pledged by member
nations of the UN. Artificial Intelligence supported solutions are suggested to assist the society and government to
achieve these goals that would work to improve the lives of the people living in the society all across the nations.
2. What is regression?
Ans. Regression is an example of rule-based AI model. In regression, the algorithm generates a mapping function from the
given data. With the help of this mapping function, we can predict the future data. For example, if we want to predict
the temperature of a day in a year, we can use past year’s temperature for that day as training data and can predict it for
the coming year. Regression is a mathematical approach to find a relationship between two or more variables. It works
with continuous data. This can be used for weather forecasting, time series modelling, etc. In order to get the best fit
results, the distance between the line and data points should be minimum.
3. Explain unsupervised learning model.
Ans. An unsupervised learning approach works on an unlabeled dataset. This means that the data which is fed to the
machine is random and there is no knowhow available about it to the trainer.
These learning models are used to identify trend, pattern and relationship in the data which is fed into it. In this model
the major features are identified by the machine, which helps the user in understanding the data. For example, in the
data of 100 cat images, if you want to understand some pattern in the data, you would need to feed this data into the
unsupervised learning model and train the machine. Once trained, the machine would identify patterns in the data.
These patterns might already be known to the user, like colour or size, or something unusual about the cats.
4. What is Evaluation? Describe the process involved in it.
Ans. Evaluation is a very important stage of AI Project designing and training where we properly test the system to find out
the efficiency and performance of the model. After the model is designed and trained then the reliability of the model
is checked using Testing Data acquired at the Data Acquisition stage. This testing data is given as an input to the newly
created AI model and the output received is checked and evaluated on the basis of:
• Accuracy
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