AI Project Cycle-week 1

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divya.khandelwal

2021-9-16 published at other category

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1.Unit 2AI Project Cycle Grade 9 Lecture 1
2.Study Plan
3.Learning Objectives: To understand how to get started with AI projects.
4.Introduction: AI Project Cycle
5.Let’s understand with the help of an example
6.Imagine! The world’s largest diamond, is in danger as Mr. X has threatened to steal it. No one is able to track Mr. X and so the situation is critical. You have been appointed as the Chief Security Officer Your job is to enhance the security of the diamond to make the area impossible for Mr X to break into and steal the diamond.
7.Now that you are aware of AI concepts, plan to use them in accomplishing your task. Start with listing down all the factors which you need to consider while framing a security system.
8.A CLIENT I M Design a Surveillance system that will identify and ring an alarm if any unauthorised person(Mr. X) tries to enter the area where the Diamond is kept.
9.While finalizing the aim of this system, you scope the problem which you wish to solve with the help of your project. This is Problem Scoping.
10.You get to know that some people are allowed to enter the area where the diamond is kept. People who can enter the premises: Maintenance people Officials VIPs, etc
11.Now, your challenge is to make sure that no unauthorized person enters the premises. Get photographs of all the authorized people Get photographs of all the unauthorized people Get photographs of the premises in which the diamond has been kept. Get photographs of all the visitors.
12.As you start collecting the photographs, you acquire data in a visual form. This data now becomes the base of your security system. Note that the data needs to be accurate and reliable as it ensures the efficiency of your system. This is known as Data Acquisition.
13.After acquiring the required data, you realize that it is not uniform.
14.Thus, you think of putting all the information collected in a simplified format for which you:
15.At this stage, you try to interpret some useful information out of the data you have acquired. For this, you explore the data and try to put it uniformly for a better understanding. This is known as Data Exploration. Data Exploration refers to the techniques and tools used to visualize data through complex statistical methods.
16.Develop a system which detects the face of a person entering the vault match it with the existing image data To do this: put all your data into the AI-enabled model train it in such a way that it alerts the officials if an unknown person tries to enter the vault
17.To implement this, you need:
18.To implement your idea, you now look at different AI-enabled algorithms which work on Computer Vision (since you are working on visual data). You go through several models and select the ones which match your requirements. After choosing the model, you implement it. This is known as Modelling stage.
19.Your surveillance system is now complete! But we need to test it…
20.You test it by sending a mix of known and unknown faces to the vault. You notice that the results were 70% correct. After evaluating this model, you work on other shortlisted AI algorithms and work on them.
21.You test algorithm to…. To ensure that they are effective in solving the given problem
22.As you move towards deploying your model in the real-world, you test it in as many ways as possible. In this stage, we evaluate each and every model tried and choose the model which gives the most efficient and reliable results. This is known as Evaluation stage. It enables continuous improvement and learning to be used for new strategies, programmes and projects
23.After proper testing, you deploy your surveillance system in the premises. Mr. X, who is unaware of the surveillance system, tries to break through the vault and gets caught in your system. You have saved the diamond! Congratulations! Mission Accomplished!
24.Recap AI Project cycle Problem Scoping: You set the goal for your AI project by stating the problem which you wish to solve with it. Data Acquisition: You go for data acquisition by collecting data from various reliable and authentic sources. Data Exploration: Since the data you collect would be in large quantities, you can try to give it a visual image of different types of representations like graphs, databases, flow charts, maps, etc. This makes it easier for you to interpret the patterns in which your acquired data follows. Data Modelling: You decide upon the type of model you would build to achieve the goal. The most efficient model is now the base of your AI project, and you can develop your algorithm around it. Evaluation and Testing : Once the modelling is complete, you now need to test your model on some newly fetched data. The results will help you in evaluating your model and, hence improving it. Finally, after evaluation, the project cycle is now complete and what you get is your AI project.
25.Assignment: Explain the concept of AI project cycle.
26.

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