Harshil Chauhan

A

Advanced Customer Analytics: Segmentation, Churn, and Predictive marketing model

Jan 2023 - May 2023 (5 months)

This Project aims to apply advanced customer analytics techniques to improve customer engagement, retention, and revenue for a retail company and focuses on three key areas: customer segmentation, predicting customer churn, and developing a predictive marketing model. To enhance customer segmentation, clustering techniques will be used to group customers based on relevant attributes, and previous campaign response rates will be analyzed. This will enable the company to better understand its customer base and tailor marketing efforts accordingly. To predict customer churn, a predictive model will be developed using machine learning algorithms. This model will analyze customer attributes to identify high-risk customers who are more likely t

B

Building Supply Chain for Covid-19 Vaccines - CaseStudy

Oct 2022 - Dec 2022 (3 months)

This project case study focuses on building a robust supply chain for the distribution of COVID-19 vaccines. The study includes four key analyses: Exploratory Data Analysis (EDA), Procurement Analysis, Inventory Analysis, and Capacity Analysis. EDA involves a comprehensive examination of the available data to identify patterns, trends, and potential challenges in the vaccine supply chain. It helps in understanding the demand patterns, logistical requirements, and optimizing the distribution network. Procurement Analysis aims to assess the efficiency and effectiveness of the procurement process for the vaccines. It involves evaluating the vendor selection, pricing strategies, and procurement timelines to ensure a reliable and cost-effecti

B

Big Data and Blockchain Technologies in Supply Chain Management with Case Studies

Sep 2022 - Dec 2022 (4 months)

This term paper explores the integration of big data and blockchain technologies in supply chain management. The paper discusses how big data, which refers to the collection, analysis, and utilization of large datasets, can be combined with analytical tools to extract value from already-available data. The paper also introduces blockchain technology, which revolutionizes the Internet by offering secure and transparent transactions through the use of cryptography and distributed ledger systems. The integration of big data and blockchain in supply chain management can address various challenges such as demand-driven management, real-time data availability, data integrity, and transparency. The paper explores the applications and benefits of b

A

Airbnb: Price Prediction Model using PySpark and AWS Cloud Services

Sep 2022 - Dec 2022 (4 months)

Rio de Janeiro is one of the most famous cities in Brazil. One of the most attractive tourist spots in the world. As tourists want to spend as less as they can for the best of amenities. Hence, this project is about the price prediction of Airbnb Rooms in Rio de Janeiro, Brazil. Predicting the price of a product is a tough challenge since very similar products have minute differences. Price prediction gets even more difficult when there is a huge range of variables. We are trying to predict prices based on relevant parameters so that we can help people make the best room choices for their money. In this, we are making an ML model of Regression for Price Prediction as we have continuous data. We are standardizing and using Standard Scaler

N

Netflix Data Warehousing and Business Intelligence

Apr 2022 - May 2022 (2 months)

In summary, the project aims to enhance Netflix's warehousing and business intelligence capabilities by leveraging a comprehensive system process, prioritization grid, opportunity matrix, detailed bus matrix, logical dimensional model, conformed dimensions, transformation rules, aggregation tables, MDDB, integrated BI design. This holistic approach will enable Netflix to extract valuable insights from its data, optimize its operations, and deliver an exceptional streaming experience to its customers.

C

Customer Analysis using Social Network Analysis

Mar 2022 - May 2022 (3 months)

The project focuses on customer analysis in the marketing strategy of Huawei through social network analysis. The report covers various aspects such as data understanding, data collection, data visualization, analytical variables, analysis, and results with recommendations. The data for analysis was obtained specifically from the social media data from Huawei's Instagram communication network. The dataset was preprocessed, and positive interaction-based links were established using Natural Language Processing. The analysis includes visualizations and measures like node degree, density, mean distance, diameter, degree centrality, betweenness centrality, eigenvector centrality, and closeness centrality. These measures provide insights into

P

Predicting Diabetic Patient using Logistic Regression

Nov 2021 - Dec 2021 (2 months)

The objective of the dataset is to diagnostically predict whether a patient has diabetes, based on certain diagnostic measurements included in the dataset. The number of patients in the database is n=768 each with 9 attribute variables. Out of the nine conditional attributes, six are due to physical examination rest of the attributes are chemical examination. This project aims to predict diabetes via supervised machine-learning methods and Logistic regression. This project also aims to propose an effective technique for the earlier detection of diabetes disease. The classification goal is to predict whether the patients in the dataset have diabetes or not. Logistic Regression is a Machine Learning classification algorithm that is used to pr

E

ER model for online marketplace business

Nov 2021 - Dec 2021 (2 months)

In the digital age, online marketplaces have become a crucial platform for buying and selling goods and services. To effectively manage the vast amount of data and ensure seamless operations, marketplaces rely on robust information systems. This project focuses on the development and implementation of an Entity-Relationship (ER) model tailored specifically to online marketplaces. The ER model serves as a blueprint for organizing and managing data, streamlining processes, and improving overall system efficiency. By leveraging the ER model, online marketplaces can enhance their system processes, optimize resource allocation, and provide a better user experience for buyers and sellers.

C

Customer Churn Prediction Model using Discriminant Analysis

Nov 2021 - Dec 2021 (2 months)

The Problem is based on the domain of the Banking sector where the bank wants to predict the Churn of a customer depending upon the previous data of the customer. By churn, it is meant that the bank wants to predict if a customer would retain or leave the bank next quarter depending upon their bank balance. It is important from a bank’s perspective in order to maintain business and customer relationships. Apart from that a bank can predict the risk of losing the customer so then primitive measures can be taken to ensure that such conditions do not erupt.

S

Smart Sewage Monitoring System

Jan 2020 - May 2020 (5 months)

Overflow of sewage on roads is been a major problem in many developed and underdeveloped cities as well. Sewage is generally considered wastewater. The response to the complaints is not properly answered or taken into account. A precautionary system is developed where this issue of sewage overflow can be reduced by early sensing of an increase in its level. The system design comprises a sensor to sense the level, a controller to command, and a communication network to register the complaints on blockage and continuous increase in the level of sewage. A database is to be maintained to record the data. We created a prototype of how the management system would work - The system rather than simply monitoring the level, generates sounds using a

Harshil Chauhan

About

Detail

Timeline

Résumé