Personal Information
Organização/Local de trabalho
Greater Los Angeles Area, CA United States
Cargo
Machine Learning guy / Data Scientist
Setor
Technology / Software / Internet
Sobre
I am a seasoned DataScientist. My area of interests is Statistical / Machine Learning modeling( Bayesian and Frequentist Modeling techniques ). In my past life I have lead initiatives and worked on solving problems related to predicting pre-emptive measure to avoid failure for improving operating efficiency in Oil n Gas Industry, social media analysis, recommendation engines, match-making using statistical models, fraud-detection, natural language processing and others.
Currently, I am curious about how to efficiently understand the true nature of predictive models and that could lead to better testing and evaluation of the same.
Marcadores
machine learning
analytics
big data
datascience
deep learning
statistics
bayesian learning
neural network
recommendation engine
uci
nlp
spark
optimization
Ver mais
Apresentações
(8)Gostaram
(38)Get hands-on with Explainable AI at Machine Learning Interpretability(MLI) Gym!
Sri Ambati
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Há 5 anos
Model Evaluation in the land of Deep Learning
Pramit Choudhary
•
Há 5 anos
IE: Named Entity Recognition (NER)
Marina Santini
•
Há 8 anos
Anomaly detection
QuantUniversity
•
Há 7 anos
Automatic Visualization - Leland Wilkinson, Chief Scientist, H2O.ai
Sri Ambati
•
Há 6 anos
Interpretable Machine Learning
Sri Ambati
•
Há 6 anos
Interpretable machine learning
Sri Ambati
•
Há 7 anos
Making Netflix Machine Learning Algorithms Reliable
Justin Basilico
•
Há 6 anos
Learning to learn - to retrieve information
Pramit Choudhary
•
Há 6 anos
Model evaluation in the land of deep learning
Pramit Choudhary
•
Há 5 anos
Production and Beyond: Deploying and Managing Machine Learning Models
Turi, Inc.
•
Há 8 anos
Icml2012 tutorial representation_learning
zukun
•
Há 11 anos
Is that a Time Machine? Some Design Patterns for Real World Machine Learning Systems
Justin Basilico
•
Há 7 anos
Data Workflows for Machine Learning - Seattle DAML
Paco Nathan
•
Há 10 anos
Lessons Learned from Building Machine Learning Software at Netflix
Justin Basilico
•
Há 9 anos
Apache Spark Model Deployment
Databricks
•
Há 7 anos
Convolutional Neural Networks (CNN)
Gaurav Mittal
•
Há 8 anos
To explain or to predict
Galit Shmueli
•
Há 11 anos
10 Lessons Learned from Building Machine Learning Systems
Xavier Amatriain
•
Há 9 anos
Recommendations for Building Machine Learning Software
Justin Basilico
•
Há 7 anos
Improving Python and Spark Performance and Interoperability: Spark Summit East talk by: Wes McKinney
Spark Summit
•
Há 7 anos
Netflix's Recommendation ML Pipeline Using Apache Spark: Spark Summit East talk by DB Tsai
Spark Summit
•
Há 7 anos
Uber's data science workbench
Ran Wei
•
Há 7 anos
Interpreting machine learning models
andosa
•
Há 8 anos
Strata 2014 Anomaly Detection
Ted Dunning
•
Há 10 anos
Deploying ml
Turi, Inc.
•
Há 9 anos
Monte Carlo Simulations in Ad-Lift Measurement Using Spark by Prasad Chalasani and Ram Sriharsha
Spark Summit
•
Há 8 anos
Lambda Architecture with Spark, Spark Streaming, Kafka, Cassandra, Akka and Scala
Helena Edelson
•
Há 9 anos
Parallel and Iterative Processing for Machine Learning Recommendations with Spark
MapR Technologies
•
Há 8 anos
Personal Information
Organização/Local de trabalho
Greater Los Angeles Area, CA United States
Cargo
Machine Learning guy / Data Scientist
Setor
Technology / Software / Internet
Sobre
I am a seasoned DataScientist. My area of interests is Statistical / Machine Learning modeling( Bayesian and Frequentist Modeling techniques ). In my past life I have lead initiatives and worked on solving problems related to predicting pre-emptive measure to avoid failure for improving operating efficiency in Oil n Gas Industry, social media analysis, recommendation engines, match-making using statistical models, fraud-detection, natural language processing and others.
Currently, I am curious about how to efficiently understand the true nature of predictive models and that could lead to better testing and evaluation of the same.
Marcadores
machine learning
analytics
big data
datascience
deep learning
statistics
bayesian learning
neural network
recommendation engine
uci
nlp
spark
optimization
Ver mais