Dive into the projects I have spearheaded, where creativity meets technology. From enhancing audio quality and image clarity to developing sophisticated predictive models, these projects showcase my ability to tackle complex challenges and deliver exceptional results through advanced methodologies

Full-Stack Portfolio Website Development

  • Designed and developed a fully responsive, dynamic portfolio website using HTML, CSS, SCSS, JavaScript, React, and Angular, showcasing proficiency in front-end technologies and modular component-based architecture.
  • Enhanced website styling and maintainability by utilizing SCSS for advanced CSS features such as variables, nesting, and mixins, ensuring clean, scalable, and efficient code for UI consistency.
  • Implemented robust state management and routing with React and Angular, optimizing the user experience and enabling seamless navigation across multiple pages, while following software engineering best practices such as version control (Git) and testing for maintainability and scalability.

  • Skills: HTML, CSS, SCSS, JavaScript, React, Angular, Software Development

Flex Bot: LLM Model (Advanced Chatbot)

  • Conducted web scraping on 30+ applications using the Google Play Scraper library, storing data securely on Amazon S3 for scalable analysis and subsequent app-related metric analysis (ratings, reviews, etc).
  • Deployed an advanced chatbot solution integrating the Langchain framework with OpenAI's GPT4 for language processing.
  • Showcased user-friendly interface using Streamlit, resulting in 25% increase in traffic to applications.

  • Skills: Python Programming, Amazon S3, Web Scraping, OpenAI, Langchain Framework, Streamlit

Netflix Stock Prediction & Competitive Analysis

  • Developed predictive models using various machine learning algorithms such as Linear Regression, ElasticNet, XGBoost, Decision Trees, and Long Short-Term Memory (LSTM) networks to forecast Netflix stock prices, achieving a high degree of accuracy in the predictions.
  • Conducted a thorough competitive analysis by comparing Netflix stock performance with other major stocks in the entertainment industry, identifying key trends and factors influencing stock prices.
  • Utilized advanced data visualization techniques to present the findings and insights from the stock price predictions and competitive analysis, facilitating better understanding and strategic decision-making.

  • Skills: Machine Learning Algorithms, Python Programming, Regression, ElasticNet, XGBoost, Time Series Forecasting, Statistical Analysis, Financial Analysis, Competitive Analysis, Data Preprocessing

Comprehensive Analysis of Environmental Impact

  • Conducted exploratory data analysis in R programming and Microsoft Excel on multiple datasets to investigate the impact of food and feed on the environment over a period of 48 years and represented analysis by making use of dashboards.
  • Collaborated to create an interactive website that showcased the project's findings and visualizations implying various data visualization tools such as Tableau, Data Wrapper, Plotly, and R-Shiny.
  • Implemented statistical models and machine learning algorithms in Python to predict future trends in food and feed production, consumption, and environmental impact.

  • Skills: R Programming, Python Programming, Exploratory Data Analysis, Data Visualizations, Tableau, Power BI, R-Shiny, Dashboards, Statistical Modeling, Jupyter Notebook

Database Management for Financial Analysis

  • Designed a normalized database project in SQL and NoSQL (MongoDB and Neo4j) to help customers compare product pricing, compute transportation cost, and make orders from over 50 stores in Boston, MA.
  • Led analysis in R and Excel and visualization in PowerBI to understand insights of orders and comparison of all 50 stores.
  • Implemented advanced SQL queries for financial reporting, including revenue analysis and cost tracking, to support strategic decision-making and identify trends and patterns.

  • Skills: SQL, MongoDB, Neo4j, Relational Database, R Programming, Tableau, Financial Analysis, EDA, Excel, Database Design

Music Genre Classification Using Neural Networks

  • Developed Python-based predictive models for music genre classification utilizing spectrograms and histograms to pre-process audio files, followed by partitioning into training and testing sets for classification using CNN and Regression techniques.
  • Conducted comprehensive statistical evaluations of multiple models' performance, identifying the CNN model as the most accurate with an 89% accuracy rate, making it the preferred choice for deployment.
  • Created a user-friendly interface using Streamlit to allow users to upload audio files and receive real-time genre predictions based on the trained model.

  • Skills: Python Programming, Convolutional Neural Networks (CNN), Data Wrangling and Preprocessing, Statistical Analysis, Machine Learning Algorithms, Data Visualization, Seaborn, Streamlit, Recommendation Systems, Classification, Jupyter Notebook

Advanced YouTube Metrics Analysis using Tableau

  • Conducted extensive data collection and aggregation of various YouTube metrics from multiple sources, followed by data wrangling and manipulation to ensure accuracy and completeness for analysis.
  • Performed in-depth analysis using advanced data processing techniques to uncover trends, patterns, and insights, facilitating strategic decision-making.
  • Developed and implemented interactive dashboards in Tableau, incorporating complex data visualizations to support dynamic analysis and decision-making strategies.

  • Skills: Tableau, Data Analysis, Data Wrangling and Manipulation, Strategic Decision-Making

AI & ML Integration in Supply Chain Management

  • Developed machine learning models using time series forecasting and SQL-based data integration to predict demand patterns and optimize inventory management across the supply chain.
  • Implemented neural networks and reinforcement learning algorithms to enhance decision-making in production scheduling and logistics routing, resulting in improved operational efficiency.
  • Utilized natural language processing and sentiment analysis on supplier data and market reports, integrating SQL databases for efficient data retrieval and analysis to identify potential risks and disruptions in the supply chain network.

  • Skills: Supply Chain, Machine Learning, Data Integration and SQL, Natural Language Processing (NLP), Deep Learning, Data Visualization.

Human Activity Monitoring With Time Series & Clustering

  • Built a Python project to accomplish Time Series Analysis and Clustering Analysis to monitor Human Activity for several activities based on various body parts of 15 different subjects.
  • Implemented feature extraction techniques to identify key patterns and trends in the time series data, facilitating the classification of distinct human activities and enhancing the clustering accuracy.
  • Evaluated performance based on Natural Visibility, Horizontal Visibility, Permutation Entropy, and Complexity.

  • Skills: Python Programming, Image Processing, Time Series Analysis, Clustering, Jupyter Notebook, Statistical Analysis, Seaborn

Twitter Data Analysis and Network Visualization

  • Extracted and transformed keyword data from textual content into a weighted adjacency matrix, enabling detailed analysis of keyword relationships and network structure, and identified top nodes by calculating degree and strength.
  • Conducted comprehensive analysis of Elon Musk's Twitter data from 2017-2022, employing word frequency analysis, Zipf's law, and bigram network graph visualization to uncover trends and patterns in social media discourse.
  • Visualized complex data using advanced plotting techniques, including histograms and log-log plots, to illustrate word frequency distributions, network characteristics, and the rank-frequency relationship.

  • Skills: Python Programming, Data Analysis, Natural Language Processing, Network Analysis, Data Visualization

Full-Stack Real-Time Video Streaming Platform

  • Built a full-stack video streaming platform deploying React, JavaScript, MongoDB to provide buffer solutions and ensure effective delivery of video by automatic resolution adjustment (from 144p to 4K)
  • Schemed a user interface with 100+ videos on cloud, allowed users to upload and stream videos, utilized Apache Spark to process videos in real-time, Snowflake to manage data and maintain documentation, Dash for managing Dashboard
  • Implemented a recommendation engine using collaborative filtering techniques to suggest personalized video content to users based on their viewing history and preferences.

  • Skills: Web Development, React, JavaScript, MongoDB, Apache Spark, Azure, Snowflake, Dash, Cloud Computing

Edge Detection Based Medical Denoising & Wavelet Domain

  • Implemented a Python project to implement machine learning models for Image Processing to aid in real-world problems to extract the edges of medical images (CT scans) of over 12000 patients in the health care domain.
  • Applied wavelet domain to differentiate the operators and identified 93% of the affected areas accurately for timely solutions.
  • Applied time series analysis to monitor disease progression and adjust healthcare strategies dynamically.

  • Skills: Python Programming, Image Processing, Time Series Analysis, Jupyter Notebook, Seaborn, Healthcare Analysis

Regression Techniques for Temperature Prediction

  • Engineered statistical techniques in Python for Time-series analysis (Clustering & Regression Analysis) using PySpark, SciPy, and sklearn for temperature and climate forecasting based on 30 years of data and A/B testing for hypothesis.
  • Conducted sensitivity analysis to evaluate how different factors influenced temperature and climate forecasts, refining the model for increased accuracy.
  • Built an algorithm by combining several regression techniques to perform statistical analysis with a validation score of 93%.

  • Skills: Regression, Time Series Analysis, Jupyter Notebook, Data Preprocessing, A/B Testing, PySpark

Classification Problem using CNN and Deep Learning

  • Developed and trained deep learning models using neural networks to classify several fruits, achieving an 82% classification accuracy.
  • Utilized a confusion matrix to evaluate model performance, providing insights into classification errors and improving model precision by fine-tuning hyperparameters.
  • Implemented data augmentation techniques to enhance the model’s robustness and generalization, increasing the accuracy of orange fruit recognition under various conditions.

  • Skills: Python Programming, Image Processing, Classification, Neural Networks, Object Detection, Jupyter Notebook, Data Preprocessing, Parameter Tuning

Image Enhancement Through Multimodality Fusion

  • Developed an image enhancement solution using native Python libraries to merge distorted images into a single high-quality image, significantly improving clarity and detail.
  • Applied advanced image processing techniques to enhance image quality, achieving an 85% improvement in visual clarity through multimodal image fusion.
  • Optimized image fusion algorithms to effectively integrate multiple image modalities, resulting in superior image resolution and reduced distortion.

  • Skills: Python Programming, Image Processing, Multimodal Image Fusion, Image Enhancement, Jupyter Notebook

Audio Processing using MATLAB

  • Optimized audio quality in MATLAB by applying algorithms that significantly improved clarity and minimized background noise.
  • Applied advanced echo cancellation methods, resulting in a reduction of reverberation and clearer audio playback.
  • Utilized filters to effectively distinguish and isolate human voices from background noise, thereby improving overall audio clarity.

  • Skills: MATLAB Programming, Audio Signal Processing, Noise Reduction

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