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DT-1 Project Report

This project report is submitted for a course on disruptive technologies. It discusses predicting wine quality using machine learning algorithms. Chapter 1 introduces data science and the problem statement. Chapter 2 discusses the dataset and algorithms used in previous literature. Chapter 3 presents the proposed framework including a flow diagram and pseudocode. Chapter 4 discusses the results, including distribution plots, heat maps, feature importance, and model performance. Chapter 5 concludes with future work possibilities. The report contains standard elements like tables of contents, figures, and references.

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38 views12 pages

DT-1 Project Report

This project report is submitted for a course on disruptive technologies. It discusses predicting wine quality using machine learning algorithms. Chapter 1 introduces data science and the problem statement. Chapter 2 discusses the dataset and algorithms used in previous literature. Chapter 3 presents the proposed framework including a flow diagram and pseudocode. Chapter 4 discusses the results, including distribution plots, heat maps, feature importance, and model performance. Chapter 5 concludes with future work possibilities. The report contains standard elements like tables of contents, figures, and references.

Uploaded by

htlt215
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as DOCX, PDF, TXT or read online on Scribd
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Project Title

A project report submitted in partial fulfilment of the


requirement for

Disruptive Technologies-1
(23ECH-102)

By
Group No - XX
S.No. UID Name Responsibility

under the guidance of

Faculty Name

UIE, Chandigarh University


Table of Contents
List of Figures………………………………………………………………..i
List of Tables………………………………………………………………...ii
Abstract……………………………………………………………………...iii

Chapter 1. Introduction………………………………………………………4
Chapter 2. Background………………………………………………………
Chapter 3. Proposed Framework……………………………………………...
Chapter 4. Results……………………………………………………………..
Chapter 5. Conclusion and Future scope………………………………………
References……………………………………………………………………..
List of Figures
Figure 1.1: Title of Figure 1.1 ……………………………………………………………
Figure 1.2: Title of Figure 1.2……………………………………………………………
Figure 2.1: Title of Figure 2.1. ……………………………………………………………
List of Tables
Table 1.1: Title of Table 1.1. ……………………………………………………………
Table 2.1: Title of Table 2.1……………………………………………………………..
Abstract

About data science

About problem

About proposed Solution

About Results
1. Chapter 1
Introduction

About Data science

Problem Statement

Objectives
2. Chapter 2
Background

Data set explanation

Algorithms used on data set

Literature Dataset Used Algorithm Used Accuracy


3. Chapter 3
Proposed Framework

Flow diagram explanation

Pseudo code

The steps are used to implement the wine quality prediction model is depicted as pseudo code

Pseudo code: Wine quality rate computing system

Input: Red and White wine dataset

Output: Quality score

Step 1: Load the datasets

Step 2: Summarize the data distribution range using Visualization tool

Step 3: Identify the prevalent features using correlation tool

Step 4: Split the input dataset into train and test

Step 5: Transform the data to fed into machine learning models

Step 6: Invoke Decision-Tree()

Step 7: Invoke Random Forest()

Step 8: Invoke KNN ()

Step 9: Invoke SVM()

Step 10: Summarize the performance in terms rating and strength of a models using metrics
4. Chapter 4
Results

Distribution Plots

Heat Map

Feature Significance/importance

Confusion Matrix/Error Plot

Compare Models
5. Chapter 5
Conclusion and Future Scope

Introductory paragraph as a guide. ...

Summarize the main ideas. ...

Appeal to the reader's emotions. ...

Include a closing sentence.

Way towards future


Github Repository Link

References

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