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ishani-ss/README.md

Hello, I'm Ishani 🦄

linkedin

Welcome to my GitHub Blog!

I'm a former Neuroscientist turned Data Scientist employed within the Government sector to wade through data, clean it and then develop machine learning models from this data to answer business questions.

The hardest part of my role is understanding what business want. The other part is understanding how the machine learning algorithms work to explain it in simple terms to non-technical audiences.

While I can't improve on the hardest part of my role on my own, I can play around with machine learning algorithms to see how they work and how best I can communicate algorithmic performance and insights.

A list of all my projects can be found below ~


Project Updates

  • 💭 Currently, I'm doing some fun research into Large Multimodal Models and optimising performance in this infrastructure.

  • ❓ Recently I finished an excellent book called "Storytelling with Data", with lessons I will employ when communicating with data in this blog.

  • 💖 Fun fact: My profile picture is a sagittal T1 MRI at midline, with filters. Or a very colourful headshot.

Completed Project List

*Large Multimodal Models for document understanding

*Random Forests Explained for Legal Audiences

*Multi-Label Classification Modelling


Pending Project List

*Experimenting with KeyBERT and H2O AutoML

*Large Multimodal Model Experimentation

Languages and Tools

CSS3 HTML5 MySQL Python Bash Linux Git JavaScript Illustrator TensorFlow Photoshop pytorch Adobe XD Keras Power Bi

Popular repositories Loading

  1. ishani-ss ishani-ss Public

    My personal repository

  2. lmms_for_document_understanding lmms_for_document_understanding Public

    Initial research into Large Multimodal Models (LMMs) for document understanding

  3. random_forests_for_legal_audiences random_forests_for_legal_audiences Public

    A two-page description of Random Forests is provided, that is suitable for legal audiences to interpret machine learning algorithms.

  4. Experimenting-with-KeyBERT-and-H2O-AutoML Experimenting-with-KeyBERT-and-H2O-AutoML Public

    Can KeyBERT keyword extraction results be filtered by cosine similarity for better downstream modelling and to reduce the number of variables in small datasets (to prevent overfitting)?

    Jupyter Notebook

  5. Large-Multimodal-Model-Experimentation Large-Multimodal-Model-Experimentation Public

    This repository contains research and experimentation on Large Multimodal Models.

  6. Multi-Label-Classification Multi-Label-Classification Public

    This repo captures experimentation with the scikit-multilearn package and its uses in multi-label classification.

    Jupyter Notebook