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  • Generatrix- A.I based data synthesizing platform
  • Delft, Netherlands

Achievements

Achievement: YOLOAchievement: Pull Sharkx2

Achievements

Achievement: YOLOAchievement: Pull Sharkx2

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adityakunar/README.md

  • 👋 Hi, I’m @adityakunar. A M.Sc Data Scientist from TU Delft

  • 🌱 I’m currently working towards bettering synthetic tabular data generation methods via GANs, read more here->Blog

  • 💞️ I’m looking to collaborate on investigating and evaluating privacy and memorization risks associated with training differential private GANs. Read more about my work on differential privacy here->Blog

  • 👀 I’m passionate about A.I, machine learning and deep learning. I've worked on the following projects:
    - Fast and Effective Image Classification using MobileNet+SSD: To achieve a fast and effective image classifier, studied the integration of the MobileNet architecture into the Single Shot Detector (SSD) framework in pytorch, check out our work here -> Blog
    - Processing GDelt Dataset in Apache Spark and AWS: Analysed how to optimally extract insights from the GDELT dataset using Apache Spark and AWS, read more here->Blog
    - A Reproduction of Dropout for Deep Neural Networks: For effectively preventing overfitting in deep neural networks, studied dropout as a regularizer for deep neural networks using pytorch, read more about our work-> Blog
    - Cyber Data Analytics: Executed effective class imbalance learning and anomoly detection for static and time-series data using python
    - Multivariate Data Analysis: Worked on MAP estimation for classifying healthy and diseases samples in ECG data, as well as assignments related to Bayesian regression, generalised linear models, Gibbs sampling and Gaussian process classification
    - Data Visualization in Tableau: Created visually appealing, user‑friendly dashboards to let end‑users explore open data about crime and policing in the UK easily and effectively
    - Research Methodology for Data Science: Worked on linear/logistic regression models and scientifically tested hypotheses in R; examined optimizing dimensionality reduction techniques like PCA for high dimensional datasets in MATLAB
    - Natural Language Processing: Built a fake news detector using python by implementing the techniques of the paper, "Emergent: a novel data-set for stance classification"

  • 📫 You may reach me at [email protected]

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  1. Deep-Learning Deep-Learning Public

    Forked from andreaalf97/DeepLearning

    Examined the effects of dropout as a regularizer to prevent overfitting for deep neural networks. Our main aim was to reproduce the findings of the original paper. We found that our reproduction ef…

    Jupyter Notebook

  2. Computer-Vision-Seminar Computer-Vision-Seminar Public

    Forked from nikhilsaldanha/pytorch-ssd

    Studied the use of MobileNet as the primary backbone architecture in the SSD framework. Evaluated performance across multiple dimensions such as computational efficiency and model accuracy by carry…

    Python

  3. Supercomputing-for-Big-Data Supercomputing-for-Big-Data Public

    Forked from abs-tudelft/sbd

    Gained an understanding of central concepts related to efficiently using Apache Spark and the Amazon Web Services (AWS) in a practical context by analyzing a large open data set and identifying way…

    Scala

  4. Cyber-Data-Analytics Cyber-Data-Analytics Public

    Forked from AnweshCR7/cda-2020

    Worked on the following topics:- Dealing with class imbalance using SMOTE while detecting credit fraud using machine learning models; anomaly detection for time-series using ARMA and PCA; detecting…

    Jupyter Notebook

  5. Multivariate-Data-Analysis Multivariate-Data-Analysis Public

    This repo contains my work on MAP estimation for classifying healthy and diseases samples in ECG data, as well as assignments related to Bayesian regression, generalised linear models, Gibbs sampli…

    Jupyter Notebook 1

  6. Research-Methodology-for-Data-Science Research-Methodology-for-Data-Science Public

    Explored statistical modelling using linear/logistic regression models and performed statistical hypothesis testing in R; learnt how to optimize the use of PCA for high dimensional datasets using N…

    HTML 1