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artificial-neural-networks-for-fraud-detection-in-supply-chain-analytics-mlpclassifier-and-keras

In this study, we aimed to detect fraudulent activities in the supply chain through the use of neural networks. The study focused on building two machine learning models using the MLPClassifier algorithm from the scikit-learn library and a custom neural network using the Keras library in Python.

chess-queens---eda-using-plotly

Dataset Details - The dataset contains details of Top women chess players in the world sorted by their Standard FIDE rating (highest to lowest above 1800 Elo) as updated in August 2020.

credit-eda-case-study

This case study aims to give us an idea of applying EDA in a real business scenario. In this case study, we develop a basic understanding of risk analytics in banking and financial services and understand how data is used to minimise the risk of losing money while lending to customers.

data-cleaning-and-preparation-of-boston-housing-dataset---python-pandas

This project involves analysis of the Boston Housing Dataset using Python's Pandas library. Data cleaning is performed by dropping genuine outliers, resetting the index, and imputing missing values with the median of the columns. It is substituted with NaN for further analysis. The objective of this project is to clean and prepare the data

data-modelling-and-dashboarding-with-ibm-cognos-analytics

digital-music-store---data-analysis-using-sql

Data Analysis project to help Chinook Digital Music Store to help how they can optimize their business opportunities and to help answering business related questions.

exploring-the-space-missions--eda-using-plotly

Introduction This DataSet was scraped from https://nextspaceflight.com/launches/past/?page=1 and includes all the space missions since the beginning of Space Race (1957).

flight-delays-prediction-models-based-on-na-ve-bayes-regression-tree-and-logistic-regression-algos

US Flight Delays Prediction Models based on Naïve Bayes, Regression Tree, and Logistic Regression Algorithms

global-sales-data-analysis-and-exploration-using-zeppelin-hdfs-and-spark

This project aimed to analyze and understand worldwide sales data through the use of Zeppelin and HDFS. The primary objective was to utilize Spark's basic Scala commands and SQL to query and manipulate the data, providing valuable insights and findings for the customer.

ibm-spss---a-comprehensive-guide-to-data-analysis-and-data-modeling

This repository provides a comprehensive guide to IBM SPSS Modeler, including an overview of its key features and functionality.

imdb-movie-data-visualisation

Python codes for IMDb movie data visualisation.

moneyball-sports-predictive-analytics-using-excel

Maximized Expected Return to Risk Ratio by building a baseball team from a catalogue of 3,000+ with several complex constraints including salary

predicting-housing-prices-using-multiple-linear-regression-and-k-nearestneighbours-knn

The goal was to accurately estimate the value of real estate and uncover relevant factors that directly influence property prices. The study used two different models, multiple linear regression and k-Nearest Neighbours (kNN), to predict housing prices.

predictive-modeling-using-sas-enterprise-miner---decision-trees

rdbms-to-graphdb---big-data-analytics-using-neo4j

This project involves migration from a traditional RDBMS to Neo4j for big data analytics. Using graph database technology, various business-critical questions are addressed, including identifying the employees who sold Tofu, the products sold with Tofu, the total number of products, top 5 products by sales, and the category with the highest sales.

simple-aged-cache

This project presents my implementation of a simple cache system that supports automatic expiration of entries.

soccer-match-predictor-end-to-end

The Match Predictor is a web application that predicts the outcomes of soccer matches using various machine learning models. The backend is written in Python with Flask, and the frontend is built using TypeScript and React.

supermarket-organic-product-purchase-prediction---data-mining-and-modeling-with-sas

This project aims to predict which customers are likely to purchase the new line of organic products offered by a supermarket. The supermarket has a customer loyalty program and collected data through a coupon incentive program for organic products. The analysis was performed using SAS Enterprise Miner.

user-occupation-and-movies-ratings-data-exploration-using-apache-hive

In this project, the objective was to analyze the "User, Occupation, Movies, and Ratings" dataset using Apache Hive. The data was processed and analyzed using Hive's SQL-like query language and MapReduce framework, making it easier to handle large datasets. The focus of the analysis was to provide a comprehensive breakdown of the data