Saran Ahluwalia
ahlusar1989
Scientist and student of Bayesian Statistics. Previously worked on problems @Patchd-Medical (@saran-ahluwalia-patchd) and @healthrhythms.
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Jupyter Notebook
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Detect self-intersecting polygons in Javascript. An implementation of the Bentley–Ottmann sweep line algorithm for detecting crossings in a set of line segments.
Driven by events, asynchronously perform computationally-intensive tasks
Experiments with Nuclear Norm Minimization
ThreeJS and Raycasting
Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"
How to calibrate your neural network classifier: Getting accurate probabilities from a classification model
Repositories
181Driven by events, asynchronously perform computationally-intensive tasks
Github Pages personal site - forked from mmistakes/minimal-mistakes
Modeling contributions in 2020
Experiments with Nuclear Norm Minimization
No description provided.
Reproducing data extraction step from published paper (prediction of sepsis on patients in the ICU) using SQL, BigQuery and MIMIC-IV database
repeat sales index
House Price Indexes in R
@MJAlexander's Fork
A jupyter notebook with some stuff on the FT
No description provided.
Machine Learning models using a Bayesian approach and often PyMC3
A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain
ThreeJS and Raycasting
Detect self-intersecting polygons in Javascript. An implementation of the Bentley–Ottmann sweep line algorithm for detecting crossings in a set of line segments.
my blog
Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy. Avoid writing scripts or custom code to deploy and update your applications— automate in a language that approaches plain English, using SSH, with no agents to install on remote systems.
This is a project for me to work on my knowledge of the Metropolis-Hastings algorithm, object-oriented programming, and creating a Python package.
Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
For MA 797
Workshop notebooks explaining how matched filtering and MCMC techniques are used to detect gravitational waves.
Source code for our paper "BLOB: a probabilistic model for recommendation that combines organic and bandit signals" published at KDD 2020.
Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"
Tutorials website compiled for KDD 2020
A simple way to calibrate your neural network.
How to calibrate your neural network classifier: Getting accurate probabilities from a classification model
Training neural models with structured signals.
Review of Some Concepts for Hierarchical Modeling
Analysis of the NYC DoE SHSAT Results 2017 - 2018
:earth_americas: machine learning tutorials (mainly in Python3)