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I'm a ComputerScience Masters student in AIML & DS with expertising in data analysis and reporting, query optimization, data modelling and data visualizations.
🚀 Skills & Expertise
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Mastering SQL to extract and analyze large datasets, turning data into actionable insights.
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Agile in Ad Hoc Analysis, providing dynamic support for business decisions.
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Designing engaging, interactive dashboards with Tableau and Excel to bring data to life.
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Proficient in Google Sheets and Excel for comprehensive data analysis and reporting.
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Advanced in Python (with Pandas and NumPy) for seamless data manipulation and cleaning.
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Expertise in EDA, leveraging Hypothesis Testing and Feature Engineering with SciPy for deeper insights.
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Innovating in Prompt Engineering and Generative AI, working with cutting-edge tools like Hugging Face 🤗.
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Continuously evolving with Machine Learning, mastering both Supervised and Unsupervised Models for predictive analytics.
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Currently deepening knowledge of Machine Learning Algorithms for enhanced decision-making.
🗂️ Explore the index of all my works, and click on the project link icon to view detailed information.
| Project Link 🫵🏼 | Tools Used | Area of Analysis | Project Description |
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| Numpy, Pandas, Matplotlib, Seaborn, scipy, KNN Imputation, SMOTE Oversampling, Decision Tree, Bagging & Bossting, RandomForest, XGboost. | Data cleaning, Exploratory Data Analysis , Data Visualization, | This repository of CAB CHRUNS - ENSEMBLE LEARNING predicts OLA driver churn using ensemble methods—Bagging (Random Forest) and Boosting (XGBoost)—with KNN imputation and SMOTE. It reveals city-wise churn trends and key performance drivers, powering smarter, data-backed retention strategies for the ride-hailing industry. |
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Numpy, Pandas, Matplotlib, Seaborn, scipy, boxcox, Anderson-Darling, Jarque_bera, Levene, Bartlett, RandomForest, XGboost. | Data cleaning, Exploratory Data Analysis , Data Visualization, Hypothesis Testing, Advanced Python, Normality Test, Variance Test | This repository of Fintech Capestone - Loan Defaulters contains the EDA of loan defaulters. It utilizes Random Forest and XGBoost to clean discrepancies, providing insights to enhance risk assessment and inform lending strategies, making it ideal for financial analysts to mitigate loan default risks. |
| Numpy, Pandas, Seaborn, scipy, sklearn, Normalization, LogisticRegression, Model optimization | EDA, Feature Engineering, Feature selection, MachineLearning, Predictive Modelling, Hyperparameter Tuning(λ), Cross_validation | This repository delves into Logistic Regression for loan approval prediction at LoanTap. It covers data preprocessing, model development, evaluation metrics, and strategic business recommendations. Explored model optimization techniques to effectively mitigate default risks. |
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Numpy, Pandas, Matplotlib, Seaborn, scipy, statsmodels, Standarization, Linear,Ridge,Lasso,ElasticNet Regression. | Exploratory Data Analysis , Data Visualization, probability & Stats, Hypothesis Testing, FeatureEngineering, MachineLearning, Predictive Modelling. | This repository provides an in-depth exploration of the predictive linear regression model tailored for IvyLeague Admission Strategy with students' data. The analysis encompasses the application of Ridge, Lasso, and ElasticNet regressions to enhance predictive accuracy and robustness. |
| Project Link 🫵🏼 | Tools Used | Area of Analysis | Project Description |
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Numpy, Pandas, Matplotlib, Seaborn, Regex, scipy, Normalization. | Data cleaning, Exploratory Data Analysis , Data Visualization, FeatureEngineering, MinMax scaler | This repository of Credit Score Computation's emphasizing the utilization of data preprocessing, feature engineering, feature selection, and weighted average methodologies to calculate a hypothetical credit score for customers, A meticulous comparison analysis to unveil intricate patterns, providing invaluable insights and metrics for decision-making with precision for bank and credit companies. |
| Numpy, Pandas, Seaborn, scipy, Hypothesis testing, Encoding, Normalization & Standarization . | Exploratoy Data Analysis , Data Visualization, probability & Stats, Hypothesis Testing, FeatureEngineering, OneHot encoding, MinMax scaler | This repository of Delhivery's logistical endeavors, emphasizing the utilization of data processing, feature extraction, and hypothesis testing methodologies, A meticulous comparison analysis of ACTUAL vs OSRM time-distance metrics, we unveil intricate patterns, providing invaluable insights and metrics for decision-making with precision. |
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| Numpy, Pandas, Seaborn, scipy , boxcox , Ttest , Chisquare , ANOVA , Kruskal-walis , Shapiro-wilk , Mannwhitney_u. | Data analysis, Data Exploration , Data Visualization, Statistics & probability,Hypothesis Testing | This repository provides a detailed exploration of Yulu Bike rentals data using Hypothesis testing, employing statistical techniques, we delve into the nuances of customer behavior, E-bikes rental patterns offering insights & key metrics to enhance understanding and inform strategic decisions. |
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Numpy, Pandas, Matplotlib.plotpy, Seaborn, Central Limit Theorem, scipy.stats, boxcox | Data analysis, Data Exploration , Data Visualization, Statistics & probability, confidence interval | This repository provides a detailed exploration of WALMART's BlackFridaySales data using the Central Limit Theorem (CLT) coupled with Confidence Interval Analysis. Leveraging statistical techniques, we delve into the nuances of customer behavior, purchase patterns. |
| Numpy, Pandas, Matplotlib.plotpy, Seaborn, statistics , probability | Data analysis, Data Exploration , Data Visualization, Descriptive Statistics & probability | This repository serves as a comprehensive solution for AEROFIT Company's Exploratory Data Analysis (EDA), employing descriptive statistics and probability to gain insights and inform strategic decisions. |
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| Numpy, Pandas, Matplotlib.plotpy, Seaborn | Data cleaning , Data analysis, Data Exploration , Data Visualization | This repository conducts an Exploratory Data Analysis (EDA) on the OTT streaming platform NETFLIX, offering insights into user behavior, content trends, and key metrics to enhance understanding and inform strategic decisions. |
| Project Link 🫵🏼 | Tools Used | Area of Analysis | Project Description |
|---|---|---|---|
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MySQL | Data analysis, Data cleaning, Data Exploration | This repo serves as the solution for some of the 8 case studies from the [#8WeekSQLChallenge](https://8weeksqlchallenge.com). It showcases my ability to tackle various SQL challenges and demonstrates my proficiency in SQL query writing and problem-solving skills. |
| Google BigQuery | Data analysis, Data Exploration | This repo serves as the solution for the Business Case Study for the giant retail store Target in Brazil. It showcases my ability to tackle SQL challenges and demonstrates my proficiency in SQL query writing and problem-solving skills and conferring Insights and Recommendations. |
| Project Link 🫵🏼 | Tools Used | Area of Analysis | Project Description |
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Tableau, Microsoft Excel | Data cleaning , Data analysis, Data Exploration , Data Visualization , Dashboard | This vizz contains the content & analysis of Financial cash flow and balance sheet of a Fintech company. |
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Microsoft Excel, Bigquery, Tableau | Data cleaning , Data analysis, Data Exploration , Data Visualization , Dashboard, Story, Video presentation | This Individual interactive dashboard leverages the comprehensive & quantitative analysis of the state in India TELANGANA to achieve a sustainable Economic Growth. Click on this Button for the Overview |
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Tableau, Microsoft Excel | Data cleaning , Data analysis, Data Exploration , Data Visualization , Dashboard | This vizz contains the analysis of the Stock prices of company META for the past five Years and prediction analysis for the next one year through Forecasting and using Model-Quantile & percentile concept of linear regression in tableau. |
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PowerBi, Microsoft Excel | Data cleaning , Data analysis, Data Exploration , Data Visualization , Dashboard | This vizz contains financial report , Budget analysis for Sara Fashion Boutique and offerred sugesstion and key strategy recommendations for the Growth . |
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Tableau, Microsoft Excel | Data cleaning , Data analysis, Data Exploration , Data Visualization , Dashboard , Story Creation | This vizz contains the content & growth analysis of the company NETFLIX and offerred sugesstion and key strategy recommendations for the Growth . |
| Project Link 🫵🏼 | Tools Used | Area of Analysis | Project Description |
|---|---|---|---|
| Microsoft Excel | Data cleaning , Data analysis, Data Exploration , Data Visualization , Dashboard | This vizz serves as the sales Analysis of Big Fashion Store named Fashio Shoppy who has branches allover Australia. (BEST viewed in Microsoft Excel fullscreen [Any Version]) |
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| Microsoft Excel | Income statement, Balance sheet, CashFlow, Debt, Equity, Terminal Value, Forcasted Valuation | This repository contains financial assessment tools designed to project future cash flows and estimate a company's valuation over a 5-year period based on Discounted Cash Flow. (BEST viewed in Microsoft Excel fullscreen [Any Version]) |
Feel free to connect with me via 👇🏼!!!
Here are some of the Tools and Languages that I use:
Here are some of the platforms where I Practice :
