Soumya Banerjee (neelsoumya)

neelsoumya

Geek Repo

Company:University of Cambridge

Location:Cambridge, UK

Home Page:https://sites.google.com/site/neelsoumya/

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complexsystemslab

Soumya Banerjee's repositories

special_topics_unconventional_AI

Special topics class on unconventional AI

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teaching_reproducible_science_R

Material and notes for teaching reproducible science in R

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ai_outreach

Resources for explaining AI to the public and outreach activities

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dsSurvivalShiny

This is a package with miscellaneous tools, a set of computational tools and a graphical user interface (GUI) for privacy preserving federated survival model meta-analysis using the DataSHIELD platform. The primary function is to enable data and model documentation.

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join_pdf_shell_script

Shell script to join multiple PDFs using ghostscript

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teaching_resources

Compilation of teaching resources

awards

Awards (feel good folder) public

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complex_stories_explanations

Complex stories as explanations for machine learning models

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CV

Curriculum Vitae

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essential_shell_scripts

Essential shell (bash) scripts

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essential_utilities_miscellaneous

Essential miscellaneous utilities

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neelsoumya

About me (Soumya Banerjee)

paper_preprints

Preprints of papers by Soumya Banerjee

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patient_stratification_explainable_AI

Explainable AI applied to patient stratification

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practical_supervised_machine_learning

A practical in R for teaching supervised machine learning

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project_ideas

Project ideas for students

public_supervised_machine_learning

A lecture on supervised machine learning

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visualization_lecture

visualization lecture

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arc_paper_blog

Blog on ARC paper

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arckit

Tools for working with the Abstraction & Reasoning Corpus

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eto-supply-chain

ETO Chip Explorer

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lasso_elasticnet_example_R

Example of LASSO and elastic net in R

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llm_resources

Resources on large language models (LLMs)

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OSGA

Open-Source Generative Agents is a community-driven fork of 'Generative Agents,' aimed at enabling compatibility with open-source Large Language Models; enhancing performance and adaptability; and introducing new relevant (optional) features

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random_forests_R

Random forests in R

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talks

Video of talks I have given

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tb-disease-modelling

Repository for code and experiments for Wadhwani AI's efforts on TB disease modelling, in partnership with Prof Nim. Final aim is to get accurate burden estimates for districts pan-India

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