• Stars
    star
    1
  • Language
    R
  • Created over 1 year ago
  • Updated over 1 year ago

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

dsSurvival 2.0 survival curves sensitivity analysis code

More Repositories

1

dsSurvival

Survival functions for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD.
R
5
star
2

dsSurvival_bookdown

A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELD
TeX
4
star
3

special_topics_unconventional_AI

Special topics class on unconventional AI
Shell
4
star
4

teaching_reproducible_science_R

Material and notes for teaching reproducible science in R
R
4
star
5

dsSurvivalbookdown

A bookdown demonstrating how to build survival models using the dsSurvival package in DataSHIELD
TeX
3
star
6

public_open_source_data_science

A repository of open source data science projects for social good
Jupyter Notebook
3
star
7

dsSurvivalClient

Survival functions (client side) for DataSHIELD. Package for building survival models, Cox proportional hazards models and Cox regression models in DataSHIELD.
HTML
3
star
8

butterfly_detector

Basic tutorials and code for teaching deep learning and machine learning
Jupyter Notebook
2
star
9

join_pdf_shell_script

Shell script to join multiple PDFs using ghostscript
Shell
2
star
10

open_data

Open data
2
star
11

mathematics

A repository of free resources to teach yourself mathematics
2
star
12

teaching_resources

Compilation of teaching resources
2
star
13

outreach_ppi

Outreach and PPI resources for explaining AI to the public
2
star
14

survival_models

A repository of code and resources for survival models
HTML
2
star
15

meditator

Miscellaneous tools for meditation
R
2
star
16

bayesian_inference_linear_mixed_effect_models_pymc3

Example code to perform linear mixed effects regression in a Bayesian setting using the PyMc3 framework
Python
2
star
17

ai_outreach

Resources for explaining AI to the public and outreach activities
2
star
18

ramanujan_number_generator

Generating Ramanujan cab numbers
PostScript
2
star
19

complex_stories_explanations

Complex stories as explanations for machine learning models
Jupyter Notebook
1
star
20

very_basic_unix

very basic UNIX commands for newbies
1
star
21

paper_preprints

Preprints of papers by Soumya Banerjee
TeX
1
star
22

neelsoumya

About me (Soumya Banerjee)
1
star
23

pymc_examples

Examples and simple scripts for probabilistic programming using PyMC3
1
star
24

life_objective_viewpoint

An objective and complex systems viewpoint of life.
1
star
25

zenAI

zenAI
1
star
26

pheatmap_example

Example scripts to generate heatmaps using the pheatmap library
R
1
star
27

perspective_epidemics_conflict_zones

Perspective on epidemics in conflict zones. Code, parameters and installation instructions.
1
star
28

programming_resources

Resources for learning and teaching programming.
1
star
29

essential_shell_scripts

Essential shell (bash) scripts
Shell
1
star
30

gaussian_process_tutorial

Tutorial and examples for Gaussian processes
1
star
31

dsMiscellaneous

Miscellaneous tools for use in DataSHIELD
R
1
star
32

basic_statistics

Repository for teaching basics of statistics for machine learning
R
1
star
33

generic_random_forest_regression

Python
1
star
34

deep_dali

Computational art for dynamical systems
NetLogo
1
star
35

TuneableCounterfactuals

Jupyter Notebook
1
star
36

cricket_scores

cricket scores
1
star
37

public_talk_AI_India

public_talk_AI_India
1
star
38

miscellaneous_interests

Miscellaneous interest
1
star
39

working_with_domain_experts

How to work with domain experts in the field of AI
1
star
40

latexcommands

Repository of latex commands
1
star
41

mathematical_models

Repository for teaching mathematical models
1
star
42

misc_papers

Miscellaneous papers (other projects)
1
star
43

awards

Awards (feel good folder) public
Shell
1
star
44

psortb_parsing

Scripts to parse output from PSortB bioinformatics package.
Python
1
star
45

basic_python

Python cheatsheet
Python
1
star
46

patient_stratification_explainable_AI

Explainable AI applied to patient stratification
Jupyter Notebook
1
star
47

Ma_paintings_writing

Ma paintings writing (Kalyani Banerjee)
1
star
48

bioinformatics_resources

Resources on bioinformatics
1
star
49

haskell

haskell
Haskell
1
star
50

project_ideas

Project ideas for students
1
star
51

visualization_lecture

visualization lecture
R
1
star
52

metaanalysis_models

Resources and code for meta-analysis models
R
1
star
53

accelerate

accelerate
1
star
54

dsSurvival2bookdown

A bookdown demonstrating how to build survival models using the dsSurvival 2.0 package in DataSHIELD
R
1
star
55

bootstrap_example_python

A simple example for bootstrapping in python and R.
Python
1
star
56

reading_list_journal_club

reading list journal club
1
star
57

dsCoxClient

Client for Cox functions in DataSHIELD
1
star
58

nlp_resources

Resources and teaching material for Natural Language Processing (NLP)
Jupyter Notebook
1
star
59

very_basic_R

very basic R for newbies
1
star
60

scmap_single_cell

1
star
61

practical_supervised_machine_learning

A practical in R for teaching supervised machine learning
R
1
star
62

public_supervised_machine_learning

A lecture on supervised machine learning
Shell
1
star
63

writing_productivity

Writing and productivity
1
star
64

lymph_node_inspired_algorithms

lymph node inspired algorithms
1
star
65

old_software

Old software
1
star
66

travel

travel
1
star
67

forecasting_port_throughput

Forecasting port throughput
Jupyter Notebook
1
star
68

abm_old

An old ABM
C++
1
star
69

essential_utilities_miscellaneous

Essential miscellaneous utilities
Shell
1
star
70

linear_mixed_effects_model_teaching

Teaching material for linear mixed effects models
1
star
71

ethical_AI

A repository of tools and resources for ethical AI
1
star
72

graphical-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.
HTML
1
star
73

getting-_started_data_science

Resources to get started in data science and teach yourself data science
1
star