Daniel Emaasit

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I am a PhD student of Transportation Engineering doing research in Urban Mobility & Planning, Travel Demand Forecasting & Modeling, Urban Data Analytics, Highway Safety and Traffic Operations from the Transportation Research Center (TRC) at the University of Nevada Las Vegas (UNLV). Broadly, my research interests involve the development of probabilistic/Bayesian machine learning methods for high-dimensional data, with applications to Urban Mobility, Transport Planning, Highway Safety, & Traffic Operations.

machine learning bayesian data science big data transport planning united nations africa

Aktivität
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Daniel Emaasit

Präsentationen

Masters Defense 2013

Sustainable Urban Transport Planning using Big Data from Mobile Phones

Introduction to Model-Based Machine Learning

exit_presentation_daniel

Introduction to Model-Based Machine Learning for Transportation

Gefällt mir

Apache® Spark™ MLlib: From Quick Start to Scikit-Learn

Building Robust, Adaptive Streaming Apps with Spark Streaming

Structuring Spark: DataFrames, Datasets, and Streaming

H2O Machine Learning and Kalman Filters for Machine Prognostics

The Joys of Clean Data with Matt Dowle

Data mining with caret package

H2O World - Generalized Low Rank Models - Madeleine Udell

H2O World - Migrating from Proprietary Analytics Software - Fonda Ingram

Intro to Apache Spark

H2O 3 REST API Overview

H2O World - Top 10 Deep Learning Tips & Tricks - Arno Candel

H2O World - Sparkling Water - Michal Malohlava

H2O World - GLM - Tomas Nykodym

H2O World - Machine Learning for non-data scientists

H2O World - PAAS: Predictive Analytics offered as a Service - Prateem Mandal

SparkR + Zeppelin

H2O World - What's New in H2O with Cliff Click

H2O World - Ensembles with Erin LeDell

Building a REST Job Server for Interactive Spark as a Service

Applying the R Language to BI and Real Time Applications

From Data to Decisions Makers: A Behind the Scenes Look at Building The Most Respected Report In Cybersecurity

Predictive Analytics as a Service- by MarketShare

The Business Economics and Opportunity of Open Source Data Science

H2O with Erin LeDell at Portland R User Group

Design Patterns for Smart Applications

Spark Summit EU 2015: Reynold Xin Keynote

Spark Under the Hood - Meetup @ Data Science London

Generalized Low Rank Models

Spark Summit EU 2015: Combining the Strengths of MLlib, scikit-learn, and R

Spark Summit EU 2015: SparkUI visualization: a lens into your application