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dsSurvival
Survival functions for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD.dsSurvival_bookdown
A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELDspecial_topics_unconventional_AI
Special topics class on unconventional AIteaching_reproducible_science_R
Material and notes for teaching reproducible science in RdsSurvivalbookdown
A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELDpublic_open_source_data_science
A repository of open source data science projects for social gooddsSurvivalClient
Survival functions (client side) for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD.butterfly_detector
Basic tutorials and code for teaching deep learning and machine learningjoin_pdf_shell_script
Shell script to join multiple PDFs using ghostscriptopen_data
Open datamathematics
A repository of free resources to teach yourself mathematicsteaching_resources
Compilation of teaching resourcesoutreach_ppi
Outreach and PPI resources for explaining AI to the publicsurvival_models
A repository of code and resources for survival modelsmeditator
Miscellaneous tools for meditationbayesian_inference_linear_mixed_effect_models_pymc3
Example code to perform linear mixed effects regression in a Bayesian setting using the PyMc3 frameworkai_outreach
Resources for explaining AI to the public and outreach activitiesramanujan_number_generator
Generating Ramanujan cab numberscomplex_stories_explanations
Complex stories as explanations for machine learning modelsvery_basic_unix
very basic UNIX commands for newbiespaper_preprints
Preprints of papers by Soumya Banerjeeneelsoumya
About me (Soumya Banerjee)pymc_examples
Examples and simple scripts for probabilistic programming using PyMC3life_objective_viewpoint
An objective and complex systems viewpoint of life.zenAI
zenAIpheatmap_example
Example scripts to generate heatmaps using the pheatmap libraryperspective_epidemics_conflict_zones
Perspective on epidemics in conflict zones. Code, parameters and installation instructions.programming_resources
Resources for learning and teaching programming.essential_shell_scripts
Essential shell (bash) scriptsgaussian_process_tutorial
Tutorial and examples for Gaussian processesdsMiscellaneous
Miscellaneous tools for use in DataSHIELDbasic_statistics
Repository for teaching basics of statistics for machine learninggeneric_random_forest_regression
deep_dali
Computational art for dynamical systemsTuneableCounterfactuals
cricket_scores
cricket scorespublic_talk_AI_India
public_talk_AI_Indiamiscellaneous_interests
Miscellaneous interestworking_with_domain_experts
How to work with domain experts in the field of AIlatexcommands
Repository of latex commandsmathematical_models
Repository for teaching mathematical modelsmisc_papers
Miscellaneous papers (other projects)awards
Awards (feel good folder) publicpsortb_parsing
Scripts to parse output from PSortB bioinformatics package.basic_python
Python cheatsheetpatient_stratification_explainable_AI
Explainable AI applied to patient stratificationMa_paintings_writing
Ma paintings writing (Kalyani Banerjee)bioinformatics_resources
Resources on bioinformaticshaskell
haskellproject_ideas
Project ideas for studentsvisualization_lecture
visualization lecturemetaanalysis_models
Resources and code for meta-analysis modelsaccelerate
acceleratedsSurvival2bookdown
A bookdown demonstrating how to build survival models using the dsSurvival 2.0 package in DataSHIELDbootstrap_example_python
A simple example for bootstrapping in python and R.reading_list_journal_club
reading list journal clubdsCoxClient
Client for Cox functions in DataSHIELDnlp_resources
Resources and teaching material for Natural Language Processing (NLP)very_basic_R
very basic R for newbiesscmap_single_cell
practical_supervised_machine_learning
A practical in R for teaching supervised machine learningpublic_supervised_machine_learning
A lecture on supervised machine learningwriting_productivity
Writing and productivitylymph_node_inspired_algorithms
lymph node inspired algorithmsold_software
Old softwaretravel
travelforecasting_port_throughput
Forecasting port throughputabm_old
An old ABMessential_utilities_miscellaneous
Essential miscellaneous utilitieslinear_mixed_effects_model_teaching
Teaching material for linear mixed effects modelsethical_AI
A repository of tools and resources for ethical AIgraphical-user-interface-for-solving-ordinary-differential-equations
This function solves a set of ordinary differential equations (ODEs) that represent a target cell limited model with a GUI. It takes as input the ODE model parameters and an input file containing experimental data. It plots the numerically integrated solution of the ODE and the sum of squared residuals between experimental data and model solution.getting-_started_data_science
Resources to get started in data science and teach yourself data scienceLove Open Source and this site? Check out how you can help us