lpatruno Goto Github PK

5420-applied-stats

Github repository for Fall 2016 offering of Applied Statistics & Probability

airline-time-analysis

Hadoop Analysis of airline on-time performance data set for Big Data Programming course final project

austindata

Analysis of austin weather and bike share data

bayesian_inference

benchm-dl

Playing with various deep learning tools and network architectures

benchm-ml

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

berg-balance-scale-analysis

Python data analysis for automated Berg Balance Scale test for gait abnormality and fall detection

bigdata-fall17

citibike-hadoop-analysis

Hadoop Java source code for my CitiBike data set analysis

citibike-hadoop-analysis-visualization

HTML/CSS/JS for my CitiBike analysis visualization

gaitdetector

Sensor collecting Android Wear application for WISDM gait research

hashtagmath

Flask website showcasing the MathQuestionTagger statistical analysis

kubernetes-cron-job

lpatruno-blog

lpatruno.com static site backend

mathquestiontagging

Data Incubator capstone project: Multi-Label Classification of Math Questions

ml-deployment-strategies

ml_final

ny_algo_music

Code samples from NY Algorithmic Music meetup

nyc-water-payment-history

Query and scrape the NYC Water Payment history website

online-math-question-tagging

Final project for CISC 6376 Design Patterns class

planout

PlanOut is a library and interpreter for designing online experiments.

pygotham2016

Code and slides for Pygotham 2016 talk

qmf-docker

Dockerfile for Quora's qmf library

rl_catnip

Reinforcement Learning for CATNIP Lab

sagemaker-course

Code for my SageMaker course.

sagemaker-workshop-420

MLinProduction SageMaker workshop hosted in April 2020

sort-problem

Sort problem and Python implementation with timing and test cases.

stats-class

Testing github pages for a marketing site

stats-fall17

tech-breakfast

My Jupyter notebook for Namely tech breakfast on Naive Bayes classification 02/06/2016. Slides at https://docs.google.com/presentation/d/1y7SLZcLU5Wy-nljxSgSLfj5tG9Hme_i4Q4ESZt_ecqM/edit?usp=sharing