B.Sc. Title Defense
Title Defence
Presented by
Md. Azibul Islam
Id: 192-15-13309
Department of CSE
Daffodil International University
Supervised by
Md. Golam Rabbany
Lecturer
Department of CSE
Daffodil International University
Title of the proposed work
 Machine Learning for Product Recommendations System.
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Objective
 To determine which features are most useful in Product
recommendation system, filtering the most demand product,
collecting and analyzing data on user behavior and activities.
 Applying a set of supervised classifiers Those include Stand-alone
models like Recommender Systems; Logistic Regression and
Analysis; Random Forest; Xgboost; Hyperparameter Tuning;
Deployment.
 Product recommendation engines analyze data about shoppers to
learn exactly what types of products and offerings interest them.
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Motivation
• Now a days touching of technology and internet people buy product
from E-Commerce site. It is increasing day by day. Buying product from
recommendation is now so popular as everyone knows its will good for
them. It also saves their time and also make sales increasing. Product
Recommendation provide a large impact on sales with time saving
system. Recently, machine learning (ML)-based product
recommendation is so popular with much benefits.
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Expected Outcomes
• Successful completion of this project will identify the suitable
supervised model for product recommendation system.
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Methodology of work
• Machine Learning
• Data Science
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THANK YOU
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