Skip to content
View mondalsudipta's full-sized avatar
🎯
Focusing
🎯
Focusing

Block or report mondalsudipta

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
mondalsudipta/README.md

Hi there, I'm Sudipta Mondal 👋

I am currently pursuing an M.Sc. in Computer Science and Engineering at BRAC University, building on a strong foundation from my bachelor's degree in the same field. Throughout my master's program, I have been focusing on machine learning, artificial intelligence, and natural language processing. I am currently involved in my master's research on self-supervised learning and have published a paper on social media sarcasm detection.

My Research Interest: My research primarily focuses on the intersection of machine learning, artificial intelligence, and natural language processing (NLP).

Key research areas are:

  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Natural Language Processing
  • Trustworthy AI
  • Self-Supervised Learning

I am open to:

  • PhD opportunities,
  • machine learning projects(development or research),
  • contributing to Machine Learning journals or conferences.

Skills:

Languages:

Java  Python  JavaScript

ML/DL

Tensorflow  scikit-learn  Fast API  NumPy  Pandas  Plotly

Database

MySQL  MSSQL

Tools and Technologies

Linux  Git 

IDEs

IntelliJ IDEA  Jupyter Notebook  Eclipse  PyCharm  Visual Studio Code 

Connect with me:

Sudipta's github stats

Pinned Loading

  1. online-hate-speech-detection online-hate-speech-detection Public

    This research uses Twitter data to develop a content analysis model, evaluating multiple machine learning models and interpreting the best one with LIME. A bi-directional LSTM with word2vec embeddi…

    Jupyter Notebook

  2. unreliable-news-detection-ML-LIME unreliable-news-detection-ML-LIME Public

    This research processed a fake news dataset, using TF-IDF and Count Vectorizer for feature extraction and evaluating multiple ML models through stratified cross-validation. Logistic Regression with…

    Jupyter Notebook

  3. FlightFarePrediction-LIME FlightFarePrediction-LIME Public

    This research develops a regression model by performing EDA and feature transformation, followed by training several machine learning models. Random Forest delivered the best performance and its pr…

    Jupyter Notebook

  4. Machine-Learning-Projects Machine-Learning-Projects Public

    These projects used machine learning for healthcare tasks, including breast cancer classification, diabetes prediction, and medical insurance cost estimation, showcasing the versatility of models l…

    Jupyter Notebook

  5. Deep-Learning-Projects Deep-Learning-Projects Public

    Neural networks were utilized for diverse classification tasks, such as predicting breast cancer malignancy and classifying handwritten digits in the MNIST dataset. Both projects demonstrated the e…

    Jupyter Notebook

  6. NLP-Projects NLP-Projects Public

    In these NLP projects, an LSTM model was used for classifying news as fake or real, and sentiment analysis was performed on customer reviews from the Amazon Fine Food dataset. Both applications hig…

    Jupyter Notebook