ahlusar1989

AdaBoost_Explorations

Implementation of Adaptive Boosting. AdaBoost is adaptive in the sense that subsequent weak learners are tweaked in favor of those instances misclassified by previous classifiers.

Akka-Play-Spark

An implementation of two NLP classifiers using Play, Spark, Akka and Scala

awesome-test-automation

A curated list of awesome test automation frameworks, tools, libraries, and software for different programming languages. Sponsored by http://sdclabs.com

bentley-ottman

Bentley Ottman Algorithm to Validate Convex and Simple Polygons

CodePenMeetupMarch2017

Using Rust and WebGL in order to Demonstrate Tessellation

CollisionsRayCasting

ThreeJS and Raycasting

CS234ReinforcementLearning

CS234 Courswork

nyc-shsat-analysis

Analysis of the NYC DoE SHSAT Results 2017 - 2018

StandfordCSC224n

Course assignments for http://web.stanford.edu/class/cs224n/index.html

sweepline

Detect self-intersecting polygons in Javascript. An implementation of the Bentley–Ottmann sweep line algorithm for detecting crossings in a set of line segments.

ahlusar1989/sweepline

Detect self-intersecting polygons in Javascript. An implementation of the Bentley–Ottmann sweep line algorithm for detecting crossings in a set of line segments.

ahlusar1989/kdd2020-calibration

How to calibrate your neural network classifier: Getting accurate probabilities from a classification model

ahlusar1989/learnable-opinion-dynamics

Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"

ahlusar1989/low-rank-matrix-recovery

Experiments with Nuclear Norm Minimization

ahlusar1989/bentley-ottman

Bentley Ottman Algorithm to Validate Convex and Simple Polygons

ahlusar1989/CS234ReinforcementLearning

CS234 Courswork

ahlusar1989/nyc-shsat-analysis

Analysis of the NYC DoE SHSAT Results 2017 - 2018

ahlusar1989/ahlusar1989.github.io

Github Pages personal site - forked from mmistakes/minimal-mistakes

ahlusar1989/bayesian_inference

Review of Some Concepts for Hierarchical Modeling

ahlusar1989/bayesian_time_series

Machine Learning models using a Bayesian approach and often PyMC3

ahlusar1989/BayesianLinearRegression

This is a project for me to work on my knowledge of the Metropolis-Hastings algorithm, object-oriented programming, and creating a Python package.

ahlusar1989/blob

Source code for our paper "BLOB: a probabilistic model for recommendation that combines organic and bandit signals" published at KDD 2020.

ahlusar1989/federal_2020_nc_campaign_donation_prediction

Modeling contributions in 2020

ahlusar1989/geocoder

Geocoder is a geocoding library, written in python, simple and consistent.

ahlusar1989/google-ml-tf-sketch-work

ahlusar1989/hpiR

House Price Indexes in R

ahlusar1989/KDD-Tutorials-2020-Deep-Robust-Anomaly-Detection

Tutorials website compiled for KDD 2020

ahlusar1989/ls-hwk

A little ditty for the folks @ LS

ahlusar1989/ma797_supplement

For MA 797

ahlusar1989/machine-learning

Repo for all coursework for Udacity Nanodegree

ahlusar1989/machine-learning-1

:earth_americas: machine learning tutorials (mainly in Python3)

ahlusar1989/mortality-inequality-decomposition

@MJAlexander's Fork

ahlusar1989/neural-structured-learning

Training neural models with structured signals.

ahlusar1989/numerical-analysis-experiments

Experiments with Advanced Techniques in Scientific Computing

ahlusar1989/reagent

A minimalistic ClojureScript interface to React.js

ahlusar1989/reproduce-sepsis-paper

Reproducing data extraction step from published paper (prediction of sepsis on patients in the ICU) using SQL, BigQuery and MIMIC-IV database

ahlusar1989/sequence_tagger_bilstm

A finger exercise with Tensorflow and Bi-LSTMS based on this paper: https://arxiv.org/pdf/1508.01991.pdf

ahlusar1989/temperature_scaling

A simple way to calibrate your neural network.

ahlusar1989/tensor-house

A collection of reference machine learning and optimization models for enterprise operations: marketing, pricing, supply chain

ahlusar1989/WhileMyMCMCGentlySamples

my blog