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ManoharVit/README.md

Giri Manohar Vemula

👨‍💻 About Me

Myself, a dedicated Master's student specializing in Data Analytical Engineering at Northeastern University. My academic journey began with a strong foundation in computer science from Vellore Institute of Technology. Fueled by a passion for data and its potential to influence decisions. Being a technology-enthusiast, I love to work in a professional environment where I can contribute myself and enrich my analytical skills according to the latest technologies and work towards achieving the organizational goals. I'm deeply enthusiastic about harnessing technology to solve complex problems and drive innovation.

My skills span across Data Wrangling, Statistical modeling, Data Integration, Machine learning, and Data visualization which are enriched by academic projects and my experience as a Python Web Developer Intern. Skilled in R (dplyr, tidyr, readr, caret), Python (Pandas, numpy, Scikit-learn, Tensor-flow, Seaborn), and Java, I excel in transforming complex data into meaningful insights. My toolkit also includes Data Analytical Tools like Microsoft Office Suite, R Studio, Power BI, Tableau, Flourish, and Data Engineering Tools such as MySQL, MongoDB, AWS, Cloud SQL, and Snowflake. These technical skills, combined with soft skills like effective communication, adaptability, problem-solving, collaboration, critical thinking, and presentation abilities, empower me to deliver comprehensive data solutions.

In my repositories, you'll find a diverse array of projects, ranging from predictive analytics models and customer segmentation strategies for Business Analysis, data quality enhancement and ETL pipeline optimization for Data Engineering, and from complex statistical analysis and machine learning models for Data Science, to data visualization and trend analysis for Data Analysis. These projects underscore my ability to collaborate effectively, communicate insights clearly to stakeholders, and contribute meaningfully to data-driven decision-making processes.

I welcome everyone to look into my work, where each repository stands as evidence of my constant commitment to the field of data. If you are seeking interest in collaborating, you are welcome to fork or contribute to my projects. Join me in engaging with and making valuable contributions to the ever-evolving realm of data science. Together, we can enhance our knowledge and skills in this captivating discipline.

🔧 Technologies & Tools

aws git java mongodb mysql opencv pandas python pytorch scikit_learn seaborn tensorflow

Certificates and Extracurricular Activities

  • Special Recognition in Data Mining Hackathon (US Offense Types)
  • Office Bearer and Poster Designer, Robotics Club, VIT University
  • Certificate of Merit, VIT-AP Engineering Clinics Projects

✉️ Contact Me

📫 How to reach me: [email protected]

linkedin.com/in/manohar511/

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  1. IE7374-MachineLearningOperations/StockPricePrediction IE7374-MachineLearningOperations/StockPricePrediction Public

    An MLOps pipeline for stock price forecasting with Airflow, DVC, and Google Cloud, featuring advanced financial models and continuous data integration.

    Jupyter Notebook 1

  2. Facial-Expression-Detection Facial-Expression-Detection Public

    Processed 29,051 images ensuring balanced emotion distribution, achieving 87% real detection.

    Jupyter Notebook

  3. ECommerce-Dive-Deep-Sales-Analysis ECommerce-Dive-Deep-Sales-Analysis Public

    In this project, we developed an ETL pipeline using Apache Airflow to process delivery data and track delayed shipments. The pipeline downloads data from an AWS S3 bucket, cleans it using Spark/Spa…

    Jupyter Notebook 1

  4. PERSONALITY-PREDICTION-TEST PERSONALITY-PREDICTION-TEST Public

    Career professionals and psychologists use this information in personality career tests for recruitment and candidate assessment. Accurate personality estimation is delicate and can be falsified to…

    Jupyter Notebook

  5. MoviETL-Data-Pipeline MoviETL-Data-Pipeline Public

    Crafted an ETL pipeline to handle 26 million user ratings and about 45,000 movies. The pipeline has the potential of ingesting data at an efficiency of 10,000 records per minute into AWS Redshift. …

  6. Crowd-Sourced-Mapping Crowd-Sourced-Mapping Public

    Using crowdsourced satellite data and ndvi values, trained a powerful multivariate classification machine learning model to classify land cover categories using'max_ndvi' and other temporal data. G…

    Jupyter Notebook 1