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ParamDesai111/README.md

Hi, 👋 I'm Param Desai

💫 About Me:

Education

Currently studying Computer Science (Stream: AI and Machine Learning) and Minor of Statistics at Carleton University.

Professional Experience

  • Currently working: Data Engineering Intern at Bank of Canada
  • Prev at Avanade Inc. as Cloud Engineering Intern

🚀 What I'm Up To

  • Using Machine Learning to do forecasting/predictions with python libraries (pandas, Numpy, scikit-learn, Tensorflow, PyTorch).
    • Statistical Models: ARIMA, SARIMA, ETS.
    • Machine Learning Models: XGBoost, Random Forest, Gradient Boosting.
    • Deep Learning Models: LSTM, Temporal Convolutional Networks (TCN), KNN.
  • Creating ETL Pipelines with big data using Kafka, Hadoop, Hive, Apache Spark, and Databricks/ADF.
  • Using Natural Language Processing (NLP) to generate sentiment features.
    • Pre-trained Models: BERT (via HuggingFace), RoBERTa, VADER (Valence Aware Dictionary for Sentiment Reasoning).
    • Topic Modeling: BERTopic, LDA.

🌐 Connect with me:

💻 Tech Stack:

  • Languages:

  • Developer Tools:

  • Libraries/Frameworks:

Pinned Loading

  1. SportsAnalyticsPipeline SportsAnalyticsPipeline Public

    Sports Analytics Platform with data ingestion, transformation with Databricks and Ingested into SQL Table. Machine Learning in Databricks for player performance forecasting

    Jupyter Notebook

  2. Health-Recommendation-System Health-Recommendation-System Public

    recommendation medicine and other health stuff to the public

    Jupyter Notebook

  3. mazeRunner mazeRunner Public

    Python

  4. Movie-Recommendation-System Movie-Recommendation-System Public

    CSV Dataset being used here, practice for when actual app being created

    Jupyter Notebook 1

  5. Fashion-Trends-Sentiment-Analysis-and-Forecasting Fashion-Trends-Sentiment-Analysis-and-Forecasting Public

    Using tweets from around the world to analyze fashion trends and predict those trends in the coming months.

    Jupyter Notebook

  6. validata validata Public

    Python automated library designed to validate, clean, and improve data quality in data engineering and data science workflows.

    Go