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gudashashank/README.md

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Hello ๐Ÿ‘‹, I'm Shashank Guda

Accomplished Data Science professional with a strong background in Machine Learning, Data Analytics, and Business Intelligence. Adept at leveraging cutting-edge technologies, including LLMs, LangChain, and Cloud platforms, to drive data-driven solutions. Proven ability to translate complex data into actionable insights, streamline processes, and optimize operations. Skilled in project management, stakeholder collaboration, and delivering high-quality results within tight deadlines. Committed to continuous learning and professional growth in the rapidly evolving field of Data Science.


๐Ÿ™‹โ€โ™‚๏ธ About Me:

  • ๐ŸŽ“ Currently a Graduate Student at Syracuse University ๐ŸŠ
  • ๐ŸŒฑ Iโ€™m currently learning LangChain, LLMs
  • ๐Ÿ’ป Interned at Inferenz as a Jr. AI/ML Engineer
  • ๐Ÿ’ผ Previously worked as an Analytics Consultant at Tredence
  • ๐Ÿ“ซ Connect with me on LinkedIn
  • โœ๏ธ My Blogs Medium

๐Ÿš€ Skills and Technologies:

Python SQL Pandas NumPy Git Power BI Tableau AWS Microsoft Azure Postgres Supabase Anaconda Apache Spark Apache Hive Keras Matplotlib mlflow PyTorch SciKit TensorFlow Microsoft Excel Microsoft PowerPoint Jira Jupyter RStudio R

๐ŸŒŸ Featured Projects:

  • Project 1: EqualEyes aims to advance image captioning technology by combining recent advances in image recognition and language modeling to generate rich and detailed descriptions beyond simple object identification.
  • Project 2: CropScan is a simple mobile tool that helps farmers and gardeners instantly check if their plants are healthy. Just snap a picture of any plant leaf, and our AI technology quickly tells you if it's healthy or sick. By catching plant diseases early, CropScan helps farmers save their crops without needing expensive expert advice.
  • Project 3: This project involves a comprehensive analysis of data from the Austin Animal Center to understand trends in animal intakes, outcomes, and stray locations. By merging and analyzing multiple structured datasets, project aims to identify factors contributing to stray animal cases and develop strategies to address the issue. The analysis includes exploratory data analysis, preprocessing, and actionable insights to improve adoption rates and animal welfare.

โ˜• Show your support

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  1. apu-sensor-failure-prediction apu-sensor-failure-prediction Public

    This project uses sensor data from metro train Auxiliary Power Units (APUs) to detect anomalies and predict potential failures. By applying K-Means clustering and LSTM Autoencoder models, it enableโ€ฆ

    Jupyter Notebook

  2. compass-assistant compass-assistant Public

    COMPASS is an AI-powered university recommendation system designed to help international students navigate the U.S. university application process. Built with Streamlit and powered by GPT-4, COMPASโ€ฆ

    Python

  3. tokyo-olympics-analysis tokyo-olympics-analysis Public

    An Azure cloud-based data analytics solution that processes and visualizes the 2021 Tokyo Olympics dataset. This end-to-end pipeline leverages Azure Data Factory for data ingestion, Data Lake Storaโ€ฆ

  4. LEAP LEAP Public

    Forked from dasaribhumika/learning-path-generator

    LEAP transforms scattered learning goals into structured pathways, guiding learners from curiosity to mastery through personalized educational journeys.

    Python

  5. EqualEyes EqualEyes Public

    The project aimed to push image captioning technology forward by combining recent advances in image recognition and language modeling to generate novel, descriptive captions that go beyond just namโ€ฆ

    1

  6. Austin_Animal_Data_Analysis Austin_Animal_Data_Analysis Public

    The analysis examines data from the Austin Animal Center on animal intakes, outcomes, and stray locations to understand trends in the city's animal population and identify reasons behind stray animโ€ฆ

    Jupyter Notebook