Personal Information
Entreprise/Lieu de travail
Washington D.C. Metro Area, MD United States
Profession
Applied Quantitative Researcher
Secteur d’activité
Government / Military
Site Web
github.com/stephenhky
À propos
Kwan-Yuet (Stephen) Ho, Ph.D. is an applied quantitative researcher with 8-year experience in machine learning, text mining, and other related data science and quantitative fields. He possesses exceptional mathematical abilities, and experience with software development. He is seeking to advance his careers in machine learning, data science and quantitative analytics.
Mots-clés
physics
machine learning
technology
helimagnets
theoretical physics
gartner hype cycle
investment
finance
market
quantum information
quantum computing
python
quantum physics
tensor network
artificial intelligence
story-telling
production
gradient descent
prototype
science
monitoring
software testing
software development
data science
#dataanalysis
#dataengineering
#it
#machinelearning
#bigdata
#datascience
balaam
sunday school
numbers
priest
moses
bible
pentateuch
traffic flow
text analytics
data mining
statistical physics
optimization
a phase
nematics
skyrmion
liquid crystal
choletorics
columnar phase
non-fermi liquid
chiral magnets
goldstone modes
condensed matter
helimagnons
nfl
Tout plus
Présentations
(7)J’aime
(15)Python tools to deploy your machine learning models faster
Jeff Hale
•
il y a 2 ans
Detecting Lateral Movement with a Compute-Intense Graph Kernel
Data Works MD
•
il y a 5 ans
Natural Language Processing with Graph Databases and Neo4j
William Lyon
•
il y a 8 ans
Machine Learning Powered by Graphs - Alessandro Negro
GraphAware
•
il y a 6 ans
Graph-Powered Machine Learning
GraphAware
•
il y a 6 ans
Nova Data Science Meetup 9-20-2017 Introduction
NOVA DATASCIENCE
•
il y a 6 ans
Nova Data Science Meetup 9-20-2017 Presentation How AI Powers the Comcast X1 Voice Interface
NOVA DATASCIENCE
•
il y a 6 ans
TENSOR DECOMPOSITION WITH PYTHON
André Panisson
•
il y a 7 ans
word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
👋 Christopher Moody
•
il y a 8 ans
Using Topological Data Analysis on your BigData
AnalyticsWeek
•
il y a 10 ans
Piotr Mirowski - Review Autoencoders (Deep Learning) - CIUUK14
Daniel Lewis
•
il y a 9 ans
Apache Spark Overview
Vadim Y. Bichutskiy
•
il y a 8 ans
Representation Learning of Vectors of Words and Phrases
Felipe Moraes
•
il y a 9 ans
Personal Information
Entreprise/Lieu de travail
Washington D.C. Metro Area, MD United States
Profession
Applied Quantitative Researcher
Secteur d’activité
Government / Military
Site Web
github.com/stephenhky
À propos
Kwan-Yuet (Stephen) Ho, Ph.D. is an applied quantitative researcher with 8-year experience in machine learning, text mining, and other related data science and quantitative fields. He possesses exceptional mathematical abilities, and experience with software development. He is seeking to advance his careers in machine learning, data science and quantitative analytics.
Mots-clés
physics
machine learning
technology
helimagnets
theoretical physics
gartner hype cycle
investment
finance
market
quantum information
quantum computing
python
quantum physics
tensor network
artificial intelligence
story-telling
production
gradient descent
prototype
science
monitoring
software testing
software development
data science
#dataanalysis
#dataengineering
#it
#machinelearning
#bigdata
#datascience
balaam
sunday school
numbers
priest
moses
bible
pentateuch
traffic flow
text analytics
data mining
statistical physics
optimization
a phase
nematics
skyrmion
liquid crystal
choletorics
columnar phase
non-fermi liquid
chiral magnets
goldstone modes
condensed matter
helimagnons
nfl
Tout plus