Page 216 - Artificial Intellegence_v2.0_Class_9
P. 216
2. Acquire data from various reliable and authentic sources that will be the base of your project as it will help in
understanding the requirements.
3. Since the data collected is big data, you can try to represent it graphically by using graphs, databases, flow
charts, maps, etc. This makes it easier for you to interpret the patterns that the acquired data follows.
4. After exploring the pattern, the next step is to decide upon the type of model to build to achieve the suitable
output.
5. Test the selected model and figure out the most efficient one.
6. Developing the algorithm on the selected model.
7. After the completion of the model, it needs to be now tested on some newly fetched data. The results will be
helpful in evaluating the model and improving it.
8. Project cycle is now complete and ready to be deployed.
Setting Goals for an AI Project
Problem scoping is the term used to define the process of selecting a problem which we might want to solve
using AI knowledge. Identifying a problem and then having a vision to solve it is called problem scoping.
Let us start scoping a problem. Look around, we are surrounded by problems, big or small. At times we don’t
feel the problem, as we are so used to them. Look around and select a theme that interests you the most from
the following diagram:
Environment Travel Entertainment Education
Tourism
Cyber Women Social Security
security Safety Welfare
Digital Agriculture Research Health
Literacy
Infrastructure Transport Traffic Disability
You can select any one from the above diagram. Further you can also select from the 17 Sustainable Development
Goals.
214 Touchpad Artificial Intelligence (Ver. 2.0)-IX

