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Transcript

The AI Project Cycle

By Saanvi Yentrapati 9C

WHAT IS AN AI PROJECT CYCLE?

The AI Project Cycle is a cycle of an AI Project which defines every step an organization must take to get value from that AI Project to get more Return on Investment.

WHAT IS IT?

Project cycle

VARIOUS STAGES OF A PROJECT CYCLE

STAGES

The various stages of an AI project cycle are as follows:

1.Problem Identification

2. Problem Scoping

3. Data Acquisition

4. Data Exploration

5. Data Modelling

6. Evaluation

7. Deployment.

FLOW CHART

1. PROBLEM SCOPING

Problem scoping is the process by which we figure out the problem that we need to solve.

1st STAGE

DATA ACQUISITION

Data Acquisition means Acquiring Data needed to solve the problem.

2nd STAGE

DATA EXPLORATION

Data Visualization is a part of this where we visualize and present the data in terms of tables, pie charts, bar graphs, line graphs, bubble chart, choropleth map etc.

3rd STAGE

MODELLING

4th STAGE

An AI model is a program or algorithm that utilizes a set of data that enables it to recognize certain patterns.

There are 2 Approaches to make a Machine Learning Model.

TWO

APPROACHES

EVALUATION

5th STAGE

The method of understanding the reliability of an API Evaluation and is based on the outputs which is received by the feeding the data into the model and comparing the output with the actual answers.

DEPLOYMENT

Deployment is the method by which you integrate a machine learning model into an existing production environment to make practical business decisions based on data.

LAST STAGE

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