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AI Project Cycle

Problem Scoping

Identifying a problem and having a vision to solve it!

Problem Scoping

Who?

What?

Where?

Why?

Data Acquisition

Collecting The Data

Data Acquisition

Surveys

Web Scraping

Sensors

Cameras

Observations

API

Data Exploration

Data exploration is an approach to understand the characteristics of a dataset using visual exploration rather than traditional data management systems.

Visualisation Tools

Excel

Fusion Charts

Big Data

Datawrapper

Power BI

Tableau

Google Data Studio

QlikView

Pictures

Modelling

An AI model is a software program that has been trained on a set of data to perform specific tasks like recognizing certain patterns.

Modelling

AI Models

Learning Based

The machine learns by itself

Learning Based

Unsupervised Machine Learning Models

These AI models are developed with the help of unsupervised machine learning

Unsupervised Machine Learning Based

Supervised Machine Learning Models:

These AI models are built using supervised machine learning

Supervised Machine Learing Models

Semi-Supervised Machine Learning

The semi-supervised machine learning models act as a middle ground between supervised and unsupervised machine learning

Semi-supervised machine learning models:

Rule Based!

Rule-based machine learning approaches include learning classifier systems, association rule learning, artificial immune systems, and any other method that relies on a set of rules, each covering contextual knowledge

Ex:An expert system might help a doctor choose the correct diagnosis based on a cluster of symptoms, or select tactical moves to play a game

Rule Based

Chart

Evaluation

AI evaluation focuses on checking whether machines do their tasks well, which has led to an important anomaly of AI.

Evaluation

Deployment

1)Boosting The Reasearch Area

2)Identifying The Areas Which Can Be Replicated

3)Identifying The Areas Of Deficiency Which Can Become The Areas For Future Research

4)Gathering Knowledge For Accumulation

Project Deployment

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