Personal Information
Unternehmen/Arbeitsplatz
Within 23 wards, Tokyo, Japan Japan
Beruf
Data Engineer at MapR Technologies #unrecruitable
Branche
Technology / Software / Internet
Webseite
www.mapr.com
Info
If there is anything I am good at, it's the ability to understand a business problem and translate it into working, state of the art technology. I combine professional level skills of a big data architect, data engineer, machine learning engineer and data scientist. In Machine learning,
Recently I've been working a lot with Hadoop (MapR's distribution) and Apache Spark, Apache Drill, Elasticsearch/Kibana and Kafka/MapR Streams for real-time event-driven processing.
On the machine learning side, I have strong practical experience with supervised learning, especially applied to unstructured (text) data in English, Japanese and French. Within these data-related specialties, I am more of ...
Tags
mapr
big data
machine learning
microservices
kafka
streaming
spark
hadoop
enterprise
h2o
apache spark
deep learning
apache hadoop
container orchestration
containers
converged
tensorflow
kubernetes
predictive maintenance
iot
real-time
sensor
data science
cep
scalable
strata singapore 2106
software architecture
flink
large scale
benchmarks
distributed
caffeonspark
java machine learning datarobot h2o
mapreduce distribué fondamental
introduction
indroduction
Mehr anzeigen
- Präsentationen
- Dokumente
- Infografiken
The Data Lake - Balancing Data Governance and Innovation
Caserta
•
Vor 7 Jahren
Creating a Modern Data Architecture
Zaloni
•
Vor 7 Jahren
Top 5 Mistakes When Writing Spark Applications
Spark Summit
•
Vor 7 Jahren
What does devops culture mean for engineers
Dave Kerr
•
Vor 5 Jahren
Data ops: Machine Learning in production
Stepan Pushkarev
•
Vor 6 Jahren
Machine Learning Success: The Key to Easier Model Management
MapR Technologies
•
Vor 6 Jahren
DevOps + DataOps = Digital Transformation
Delphix
•
Vor 5 Jahren
DataOps: Nine steps to transform your data science impact Strata London May 18
Harvinder Atwal
•
Vor 6 Jahren
DataOps: An Agile Method for Data-Driven Organizations
Ellen Friedman
•
Vor 6 Jahren
Human in the loop: a design pattern for managing teams working with ML
Paco Nathan
•
Vor 6 Jahren
Bridging the Gap Between Data Science & Engineer: Building High-Performance Teams
ryanorban
•
Vor 8 Jahren
Transforming Insurance Analytics with Big Data and Automated Machine Learning
Cloudera, Inc.
•
Vor 7 Jahren
Building Streaming Data Applications Using Apache Kafka
Slim Baltagi
•
Vor 6 Jahren
Hype vs. Reality: The AI Explainer
Luminary Labs
•
Vor 7 Jahren
KEY CONCEPTS FOR SCALABLE STATEFUL SERVICES
Mykola Novik
•
Vor 6 Jahren
Running Apache Zeppelin production
Vinay Shukla
•
Vor 6 Jahren
Deploying deep learning models with Docker and Kubernetes
PetteriTeikariPhD
•
Vor 7 Jahren
Deep Learning - Convolutional Neural Networks
Christian Perone
•
Vor 8 Jahren
Python for Image Understanding: Deep Learning with Convolutional Neural Nets
Roelof Pieters
•
Vor 8 Jahren
Deep learning - Conceptual understanding and applications
Buhwan Jeong
•
Vor 9 Jahren