Here you can check some of my projects which helped me improve my expertise in the Artificial Intelligence domain.

Featured Projects

Preludd Data Challenge

  • Analyzed and categorized customers based on their transactional behavior and demographic factors into different payment profiles
  • Built real-time dashboards to explain current payment profiles and recommend Alternative Payments Methods as part of Digital Transformation
  • Developed a python application to view the summary of the transactions data based on the selected filters

TOOLS USED: Jupyter Notebook, Python, Dataiku DSS, Tableau Desktop, Streamlit

Projects

Musée d’Orsay and Musée de l’Orangerie - Data Vizualization Challenge

  • Combined data from various resources, cleaned them and enriched them using various tools abnd techniques
  • Analysed the cleaned data to find lot of useful trens abd patterns to recommend solutions and improvements
  • Performed web scraping of Trip Advisor reviews to observe what people speak about Musée d’Orsay and Musée de l’Orangerie

TOOLS USED: Tableau Desktop, Tableau Prep, RStudio, Jupyter Notebook, MS Excel

Projects

Netflix Recommendation System

  • Developed a movie recommendation system for Netflix in R using two different approaches (User-Based Collobarative Filtering and Matrix Factorization)
  • Evaluated the performance of two recommendation systems using ROC Curve and accuracy
  • Built prototypes of the recommendation systems using R shiny with a convenient User Interface

TOOLS USED: R, RStudio, Tableau Desktop

Projects

Other Projects

Walton Analytics - Product Performance and Consumer Behavior Dashboard

  • Merged data from different possible sources, cleaned the data and enriched it using Tableau Prep Builder
  • Performed cohort analysis on the sales data to track the movement and flow of customers between differenmt quarters
  • Perfomed RFM analysis to segment the customers into 5 different categories based on the managerial comfort and explored their overall profile
  • Computed Customer Lifetime Value of all the customers and projevcted it to next 6 years based on the consumer behavior and their churn rate

TOOLS USED: Tableau Desktop, Tableau Prep Builder, RStudio

Baker’s Database Analysis for HR

  • Developed SQL queries for the requirements by HR from an employee database of 7 different tables and arouns 3 million entries
  • Derived insights from the extracted data using Tableau Desktop to provide recommendations to the HR
  • Provided recommendations to improve employee retainment in the company

TOOLS USED: MySQL Workbench, Tableau Desktop

CDiscount - Data Vizualization

  • Cleaned and enriched the dataset using Tableau Prep Builder
  • Compared the sales trend of CDiscount in France with other countries
  • Explored the data, found the profit generating products and loss creating products
  • Followed almost all the data visualization principles to obtain clutter free, clear data viz

TOOLS USED: Tableau Desktop, Tableau Prep Builder

Embracing Subcultures - The success of Burger King

  • Performed a case study on the series of marketing campaigns by Burger King over years embracing the subcultures existing within their customer profiles
  • Researched the different kinds of subcultures they have utilized and the response among their customers
  • Developed different methodologies on how they would have utilized the power of big data to perform these tasks

TOOLS USED: Google Sheets, Google Slides

Quora Duplicate Question prediction

  • Repeated questions are one of the greatest complications of Quora. It leads to confusion and poor reach
  • I processed the data using TF-IDF vectorizer and fit the model on various classification models
  • Conventional logistic regression seem to give better solutions

TOOLS USED: Sklearn, pandas, numpy

Whatsapp Frequent Chat analysis

  • Developed a model which can analyze whatsapp chats and deliver us valuable insights
  • Determined the frequently used words, most active days and most active time of the day
  • Working on determining the sentiment of chat and predicting the relationship based on the chat

TOOLS USED: Sklearn, pandas, numpy, matplotlib

Heart disease prediction

  • Trained a ML model to predict the possibility of occurance of heart disease for a person based on his demographic attributes
  • Some of the features used include cholestrol level, age, weight, gender, heart beat rate etc. and achieved 85% accuracy on the validation set

TOOLS USED: sklearn, numpy, pandas, seaborn

Tourism data analyis

  • Performed data analysis on the world tourism data using SAS to uncover some hidden facts
  • Found out the countries with maximum share of tourism attraction, country which generates maximum revenue, country which spends the maximum on tourism industry
  • TOOLS USED: SAS

Malaria detection from microscope images

  • Trained and improved the performance of a CNN architecture using various image augmentation techniques and optimizers
  • Achieved an training and validation accuracy of both 94.5%

TOOLS USED: Keras, pickle, numpy, matplotlib

Digit recognizer web application

  • Trained a custom developed CNN architecture to train on MNIST dataset
  • The model is then served using flask to predict the digits on local server

TOOLS USED: Keras, pickle, numpy

Stackoverflow pragramming language classification

  • Used questions and its respective programming lanuages to train a machine learning model with TF-IDF vectorizer
  • Achieved 92% accuracy on predicting the programming langauge given its questions.

TOOLS USED: sklearn, scipy, NLTK, pandas

Cat vs no-cat classifier

  • Trained a CNN model to predict between cats and non-cats images
  • The model achieved a 91% accuracy in identifying

TOOLS USED: Keras, pickle, numpy

Text exploration using Topic Modelling

  • Performed Topic modelling on a set of documents using LSA, LDA and NMF with available packages
  • Implemented topic modelling papeers such as PAM, pLSA in python

TOOLS USED: sklearn, pandas, numpy, scipy

Indian Restaurant Market Analysis

  • Preprocessd and feature engineered the data on Indian Restaurants spread across various cities
  • Fit a model to determine the overall rating based on the most relevant features

TOOLS USED: dplyr, ggplot2

Customer Churn Prediction

  • Exploed the data to detremine the significant features among the given features
  • Model is fit using classification methods and the results are compared

TOOLS USED: Sklearn, pandas, numpy, matplotlib, seaborn

Design of Front and Rear Suspension Geometry for All-terrain vehicles

  • Unequal Unparallel double wishbone system and H arm with camber link suspension system has been for Front and Rear Suspension Geometry respectively based on the design considerations
  • The system is designed using Solidworks and is analysed using ANSYS and MATLAB

TOOLS USED: Solidworks, ANSYS, Lotus Shark

Development of Part Identification System of Baja vehicle components

  • In a single baja vehicle more than 500 components are being used. Unnecessary time is used for searching different components during assembly
  • So, various components are named using Hybrid Part Identification systems and are grouped together based on the frequency of usage
  • This decreased the time consumption by many folds

TOOLS USED: MS Excel

Optimisation of Front and Rear Uprights for All-terrain vehicles

  • Based on the load applied and fatigue life, structural design and sectional thickness has been modified to minimise the material usage without trading off the steering performance of the vehicle
  • Final design is chosen based upon a number of iterations results and in accordance with suspension parameters too

TOOLS USED: Solidworks, ANSYS

Intelligent Anti-theft System for Two Wheelers

  • Incase, if a two wheeler is attempted or subjected to theft, our installed set-up captures the snap of the intruder and sends the snap to the owner’s phone along with the dynamic GPS coordinates of the two wheeler using GSM

TOOLS USED: Arduino UNO R3

Design and Analysis of Hydrogen Propelled Mobility Vehicle

  • A parallel hybrid two wheeler powered by both Li polymer battery with a rated capacity of 20Ah (based on our requirement) and PEMFC has been modeled with custom designed chassis, suspension, brakes and storage tank.
  • Material for each component has been chosen from numerous analysis of the components’ solid model.
  • Pedal force, brake force distribution, stopping distance and brake power are calculated theoretically.
  • With a fixed wheel base of 1.32m and load distribution calculated based on brake power, all the suspension parameters such as motion ratio, corner weight, wheel rate, spring rate are calculated.
  • These parameters are optimized using MS Excel and Matlab Simulink.
  • The chassis body dimensions and cross sections are chosen based on Taguchi method.
  • Real effort has been taken to measure the real dimensions of the chassis based on the ergonomic comfort of many persons of distributed age and size.

TOOLS USED: Soliworks, ANSYS, Minitab, Matlab Simulink, MS Excel

Design and Analysis of on-board high pressure compressed hydrogen storage tank

  • After finalizing the hybrid vehicle architecture and storage pressure of 700 bar, power required to propel a payload of 180 kg was calculated.
  • Comparing the heat of combustion of hydrogen and the energy needed to be produced, the mass of hydrogen required is calculated to be 1.2 kg.
  • Volume of hydrogen required is calculated and compared by Ideal gas equation, van Der Wall’s equation and generalized comparability chart.
  • A triple composite layer tank is chosen with specific dimensions after numerous iterations on ANSYS.
  • Finally, analytical simulation of burst test, crush test is carried out on the final model to ensure its endurance

TOOLS USED: Soliworks, ANSYS, Matlab Simulink, MS Excel