SlideShare a Scribd company logo
1 of 52
Download to read offline
Taegyun Jeon
TensorFlow Dev Summit Extended Seoul / 2017.02.22
R&D Center, Satrec Initiative
TensorFlow:
TensorBoard & Keras
GDG Meetup in February
Contents
 Integrating Keras & TensorFlow: The Keras Workflow,
Expanded
▫ Speaker: Francois Chollet
 Hands-on TensorBoard
▫ Speaker: Dandelion Mané
▫ Code & Slide: https://goo.gl/San2uR
 All contents are provided from TensorFlow Dev Summit 2017
(https://events.withgoogle.com/tensorflow-dev-summit/)
Page 2[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras
Keras
 An API spec for building deep learning models across many
platforms
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 3
Keras의 인기 비결?
 간편함
 간결함
 TF의 잦은 API 변경
 연구자와 개발자의
의사소통 도구
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 4
tf.keras
 Keras는 결국 TensorFlow의 품으로!
 TensorFlow layers = Keras layers
 Keras Model
▫ Sequence model and functional model API
 TensorFlow 기능과 통합 가능
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 5
https://www.tensorflow.org/api_docs/python/tf/contrib/learn/Experiment
Keras 사용자들에게 어떤 일들이?
 TensorFlow와 Keras사이에서 고민하지 않으셔도 됩니다.
 TF와 Keras의 장단점을 파악해서 섞어서 쓰세요.
 Distributed Training, Cloud ML, Hyperparameter setting,
TF-Serving
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 6
https://blog.keras.io/keras-as-a-simplified-interface-to-tensorflow-tutorial.html
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 7
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 8
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 9
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 10
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 11
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 12
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 13
Keras Example: Video QA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 14
Keras Example: Visual VQA
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 15
More Examples
 Keras Blog
▫ https://blog.keras.io/
 Keras API (keras.applications)
▫ https://keras.io/applications/
 Keras Example Directories
▫ https://github.com/fchollet/keras/tree/master/examples
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 16
Keras: Summary
 TF 사용자: 손쉬운 high-level api 사용 가능
 Keras 사용자: 모델만 keras로 만들고 이후 운영은 TF로 가능
 버전 변경 계획
▫ tf.contrib.keras (TF 1.1 / 올해 3월 중)
▫ tf.keras (TF 1.2)
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 17
TensorBoard
 TensorBoard를 이용해서 얻는 장점
▫ Debug: 내부를 알기 힘든 딥러닝 모델을 눈으로 확인
▫ Hyperparameter Tuning
▫ Visualize inference results
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 18
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 19
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 20
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 21
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 22
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 23
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 24
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 25
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 26
엄청 복잡해보이네요
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 27
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 28
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 29
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 30
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 31
이제 레이어별로
깔끔해졌습니다.
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 32
이전과 비교해봐도
눈에 잘 들어옵니다
TensorBoard: MNIST Example
 tf.summary.scalar
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 33
 tf.summary.image
 tf.summary.audio  tf.summary.histogram
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 34
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 35
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 36
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 37
정확도가 엉망이군요!
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 38
Cross-entropy도 뭔가
이상하죠?
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 39
Convolution layer가
변하지 않았음을
알 수 있습니다.
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 40
Histogram도 역시 마
찬가지군요
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 41
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 42
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 43
이제 제대로
학습이 되는군요
TensorBoard: MNIST Example
 Hyperparameter search
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 44
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 45
다양한 run을 기록
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 46
Hyperparameter를 찾을땐
epoch을 조금만 설정해서
초기 성능만 보고
ckpt 관리 및 추가학습
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 47
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 48
TensorBoard: MNIST Example
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 49
TensorBoard
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 50
TensorBoard: Summary
 Debug
▫ name_scope 정의와 tensor의 name 붙이기를 생활화
▫ Summary 기능을 활용
• Scalar, Image, Audio, Histogram
 Hyperparameter search
▫ 다양한 run을 짧게 돌려보는 것을 권장
▫ 파라미터 뿐만 아니라, 모델 형태에도 적용 가능
 Embedding visualization
▫ 표현하기 힘든 내용은 가시화!
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 51
Q & A
Any Questions?
[TensorFlow Dev Summit Extended] TensorFlow: TensorBoard & Keras Page 52

More Related Content

What's hot

Introduction to Apache Tajo: Future of Data Warehouse
Introduction to Apache Tajo: Future of Data WarehouseIntroduction to Apache Tajo: Future of Data Warehouse
Introduction to Apache Tajo: Future of Data WarehouseJihoon Son
 
Hadoop Architecture in Depth
Hadoop Architecture in DepthHadoop Architecture in Depth
Hadoop Architecture in DepthSyed Hadoop
 
Improve Presto Architectural Decisions with Shadow Cache
 Improve Presto Architectural Decisions with Shadow Cache Improve Presto Architectural Decisions with Shadow Cache
Improve Presto Architectural Decisions with Shadow CacheAlluxio, Inc.
 
Toronto meetup 20190917
Toronto meetup 20190917Toronto meetup 20190917
Toronto meetup 20190917Bill Liu
 
Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...
Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...
Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...Databricks
 
Data Science Stack with MongoDB and RStudio
Data Science Stack with MongoDB and RStudioData Science Stack with MongoDB and RStudio
Data Science Stack with MongoDB and RStudioWinston Chen
 
Apache Tajo on Swift: Bringing SQL to the OpenStack World
Apache Tajo on Swift: Bringing SQL to the OpenStack WorldApache Tajo on Swift: Bringing SQL to the OpenStack World
Apache Tajo on Swift: Bringing SQL to the OpenStack WorldJihoon Son
 
Lightning Talk: MongoDB Migration Strategies
Lightning Talk: MongoDB Migration StrategiesLightning Talk: MongoDB Migration Strategies
Lightning Talk: MongoDB Migration StrategiesMongoDB
 
SchemEX - Creating the Yellow Pages for the Linked Open Data Cloud
SchemEX - Creating the Yellow Pages for the Linked Open Data CloudSchemEX - Creating the Yellow Pages for the Linked Open Data Cloud
SchemEX - Creating the Yellow Pages for the Linked Open Data CloudAnsgar Scherp
 
HBaseCon 2015: Solving HBase Performance Problems with Apache HTrace
HBaseCon 2015: Solving HBase Performance Problems with Apache HTraceHBaseCon 2015: Solving HBase Performance Problems with Apache HTrace
HBaseCon 2015: Solving HBase Performance Problems with Apache HTraceHBaseCon
 
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017StampedeCon
 
MongoDB-Migration-Strategies
MongoDB-Migration-StrategiesMongoDB-Migration-Strategies
MongoDB-Migration-Strategiesandyjwoodard
 
Big data in the cloud
Big data in the cloudBig data in the cloud
Big data in the cloudBen Sullins
 
Query optimization in Apache Tajo
Query optimization in Apache TajoQuery optimization in Apache Tajo
Query optimization in Apache TajoJihoon Son
 
Deep dive into deeplearn.js
Deep dive into deeplearn.jsDeep dive into deeplearn.js
Deep dive into deeplearn.jsKai Sasaki
 
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...MLconf
 

What's hot (20)

Introduction to Apache Tajo: Future of Data Warehouse
Introduction to Apache Tajo: Future of Data WarehouseIntroduction to Apache Tajo: Future of Data Warehouse
Introduction to Apache Tajo: Future of Data Warehouse
 
Google's Dremel
Google's DremelGoogle's Dremel
Google's Dremel
 
Hadoop Architecture in Depth
Hadoop Architecture in DepthHadoop Architecture in Depth
Hadoop Architecture in Depth
 
Improve Presto Architectural Decisions with Shadow Cache
 Improve Presto Architectural Decisions with Shadow Cache Improve Presto Architectural Decisions with Shadow Cache
Improve Presto Architectural Decisions with Shadow Cache
 
Toronto meetup 20190917
Toronto meetup 20190917Toronto meetup 20190917
Toronto meetup 20190917
 
Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...
Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...
Strata NYC 2015: Sketching Big Data with Spark: randomized algorithms for lar...
 
Data Science Stack with MongoDB and RStudio
Data Science Stack with MongoDB and RStudioData Science Stack with MongoDB and RStudio
Data Science Stack with MongoDB and RStudio
 
Apache Tajo on Swift: Bringing SQL to the OpenStack World
Apache Tajo on Swift: Bringing SQL to the OpenStack WorldApache Tajo on Swift: Bringing SQL to the OpenStack World
Apache Tajo on Swift: Bringing SQL to the OpenStack World
 
Lightning Talk: MongoDB Migration Strategies
Lightning Talk: MongoDB Migration StrategiesLightning Talk: MongoDB Migration Strategies
Lightning Talk: MongoDB Migration Strategies
 
SchemEX - Creating the Yellow Pages for the Linked Open Data Cloud
SchemEX - Creating the Yellow Pages for the Linked Open Data CloudSchemEX - Creating the Yellow Pages for the Linked Open Data Cloud
SchemEX - Creating the Yellow Pages for the Linked Open Data Cloud
 
HBaseCon 2015: Solving HBase Performance Problems with Apache HTrace
HBaseCon 2015: Solving HBase Performance Problems with Apache HTraceHBaseCon 2015: Solving HBase Performance Problems with Apache HTrace
HBaseCon 2015: Solving HBase Performance Problems with Apache HTrace
 
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
End-to-end Big Data Projects with Python - StampedeCon Big Data Conference 2017
 
MongoDB-Migration-Strategies
MongoDB-Migration-StrategiesMongoDB-Migration-Strategies
MongoDB-Migration-Strategies
 
RubiX
RubiXRubiX
RubiX
 
Big data in the cloud
Big data in the cloudBig data in the cloud
Big data in the cloud
 
Query optimization in Apache Tajo
Query optimization in Apache TajoQuery optimization in Apache Tajo
Query optimization in Apache Tajo
 
Deep dive into deeplearn.js
Deep dive into deeplearn.jsDeep dive into deeplearn.js
Deep dive into deeplearn.js
 
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...
Mathias Brandewinder, Software Engineer & Data Scientist, Clear Lines Consult...
 
Xephon K A Time series database with multiple backends
Xephon K A Time series database with multiple backendsXephon K A Time series database with multiple backends
Xephon K A Time series database with multiple backends
 
As simple as Apache Spark
As simple as Apache SparkAs simple as Apache Spark
As simple as Apache Spark
 

Viewers also liked

Lecture5 Expert Systems And Artificial Intelligence
Lecture5 Expert Systems And Artificial IntelligenceLecture5 Expert Systems And Artificial Intelligence
Lecture5 Expert Systems And Artificial IntelligenceKodok Ngorex
 
Introduction to CLIPS Expert System
Introduction to CLIPS Expert SystemIntroduction to CLIPS Expert System
Introduction to CLIPS Expert SystemMotaz Saad
 
Expert Systems
Expert SystemsExpert Systems
Expert Systemsosmancikk
 
Electricity price forecasting with Recurrent Neural Networks
Electricity price forecasting with Recurrent Neural NetworksElectricity price forecasting with Recurrent Neural Networks
Electricity price forecasting with Recurrent Neural NetworksTaegyun Jeon
 
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016Taehoon Kim
 

Viewers also liked (6)

Lecture5 Expert Systems And Artificial Intelligence
Lecture5 Expert Systems And Artificial IntelligenceLecture5 Expert Systems And Artificial Intelligence
Lecture5 Expert Systems And Artificial Intelligence
 
Introduction to CLIPS Expert System
Introduction to CLIPS Expert SystemIntroduction to CLIPS Expert System
Introduction to CLIPS Expert System
 
Expert Systems
Expert SystemsExpert Systems
Expert Systems
 
Expert Systems
Expert SystemsExpert Systems
Expert Systems
 
Electricity price forecasting with Recurrent Neural Networks
Electricity price forecasting with Recurrent Neural NetworksElectricity price forecasting with Recurrent Neural Networks
Electricity price forecasting with Recurrent Neural Networks
 
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
 

Similar to Google Dev Summit Extended Seoul - TensorFlow: Tensorboard & Keras

TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...
TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...
TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...Edureka!
 
TonY: Native support of TensorFlow on Hadoop
TonY: Native support of TensorFlow on HadoopTonY: Native support of TensorFlow on Hadoop
TonY: Native support of TensorFlow on HadoopAnthony Hsu
 
Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017
Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017
Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017Codemotion
 
Tensorflow in production with AWS Lambda
Tensorflow in production with AWS LambdaTensorflow in production with AWS Lambda
Tensorflow in production with AWS LambdaFabian Dubois
 
High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017
High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017
High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017Chris Fregly
 
The Flow of TensorFlow
The Flow of TensorFlowThe Flow of TensorFlow
The Flow of TensorFlowJeongkyu Shin
 
Terraform AWS modules and some best-practices - May 2019
Terraform AWS modules and some best-practices - May 2019Terraform AWS modules and some best-practices - May 2019
Terraform AWS modules and some best-practices - May 2019Anton Babenko
 
GitHub as a Landing Page
GitHub as a Landing Page GitHub as a Landing Page
GitHub as a Landing Page Pronovix
 
TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...
TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...
TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...Catalyst
 
DevOps-Redefining your IT Strategy-28thJan15
DevOps-Redefining your IT Strategy-28thJan15DevOps-Redefining your IT Strategy-28thJan15
DevOps-Redefining your IT Strategy-28thJan15Edureka!
 
OpenStack Trove Update - Juno, Kilo and Beyond
OpenStack Trove Update - Juno, Kilo and BeyondOpenStack Trove Update - Juno, Kilo and Beyond
OpenStack Trove Update - Juno, Kilo and BeyondOpenStack_Online
 
Overview of TensorFlow For Natural Language Processing
Overview of TensorFlow For Natural Language ProcessingOverview of TensorFlow For Natural Language Processing
Overview of TensorFlow For Natural Language Processingananth
 
Docker + Tenserflow + GOlang - Golang singapore Meetup
Docker + Tenserflow + GOlang - Golang singapore MeetupDocker + Tenserflow + GOlang - Golang singapore Meetup
Docker + Tenserflow + GOlang - Golang singapore Meetupsangam biradar
 
Terraform 0.12 + Terragrunt
Terraform 0.12 + TerragruntTerraform 0.12 + Terragrunt
Terraform 0.12 + TerragruntAnton Babenko
 
TensorFlowOnSpark: Scalable TensorFlow Learning on Spark Clusters
TensorFlowOnSpark: Scalable TensorFlow Learning on Spark ClustersTensorFlowOnSpark: Scalable TensorFlow Learning on Spark Clusters
TensorFlowOnSpark: Scalable TensorFlow Learning on Spark ClustersDataWorks Summit
 
High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...
High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...
High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...Chris Fregly
 
Webinar: DevOps - Redefining your IT Strategy
Webinar: DevOps - Redefining your IT StrategyWebinar: DevOps - Redefining your IT Strategy
Webinar: DevOps - Redefining your IT StrategyEdureka!
 

Similar to Google Dev Summit Extended Seoul - TensorFlow: Tensorboard & Keras (20)

TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...
TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...
TensorFlow Tutorial | Deep Learning Using TensorFlow | TensorFlow Tutorial Py...
 
TonY: Native support of TensorFlow on Hadoop
TonY: Native support of TensorFlow on HadoopTonY: Native support of TensorFlow on Hadoop
TonY: Native support of TensorFlow on Hadoop
 
Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017
Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017
Container orchestration: the cold war - Giulio De Donato - Codemotion Rome 2017
 
Why LaTeX
Why LaTeXWhy LaTeX
Why LaTeX
 
Callbacks part2
Callbacks part2Callbacks part2
Callbacks part2
 
Tensorflow in production with AWS Lambda
Tensorflow in production with AWS LambdaTensorflow in production with AWS Lambda
Tensorflow in production with AWS Lambda
 
High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017
High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017
High Performance Distributed TensorFlow with GPUs - NYC Workshop - July 9 2017
 
The Flow of TensorFlow
The Flow of TensorFlowThe Flow of TensorFlow
The Flow of TensorFlow
 
Terraform AWS modules and some best-practices - May 2019
Terraform AWS modules and some best-practices - May 2019Terraform AWS modules and some best-practices - May 2019
Terraform AWS modules and some best-practices - May 2019
 
GitHub as a Landing Page
GitHub as a Landing Page GitHub as a Landing Page
GitHub as a Landing Page
 
TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...
TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...
TechSEO Boost 2018: Implementing Hreflang on Legacy Tech Stacks Using Service...
 
DevOps-Redefining your IT Strategy-28thJan15
DevOps-Redefining your IT Strategy-28thJan15DevOps-Redefining your IT Strategy-28thJan15
DevOps-Redefining your IT Strategy-28thJan15
 
OpenStack Trove Update - Juno, Kilo and Beyond
OpenStack Trove Update - Juno, Kilo and BeyondOpenStack Trove Update - Juno, Kilo and Beyond
OpenStack Trove Update - Juno, Kilo and Beyond
 
Overview of TensorFlow For Natural Language Processing
Overview of TensorFlow For Natural Language ProcessingOverview of TensorFlow For Natural Language Processing
Overview of TensorFlow For Natural Language Processing
 
Docker + Tenserflow + GOlang - Golang singapore Meetup
Docker + Tenserflow + GOlang - Golang singapore MeetupDocker + Tenserflow + GOlang - Golang singapore Meetup
Docker + Tenserflow + GOlang - Golang singapore Meetup
 
Terraform 0.12 + Terragrunt
Terraform 0.12 + TerragruntTerraform 0.12 + Terragrunt
Terraform 0.12 + Terragrunt
 
TensorFlowOnSpark: Scalable TensorFlow Learning on Spark Clusters
TensorFlowOnSpark: Scalable TensorFlow Learning on Spark ClustersTensorFlowOnSpark: Scalable TensorFlow Learning on Spark Clusters
TensorFlowOnSpark: Scalable TensorFlow Learning on Spark Clusters
 
Basics of LaTeX
Basics of LaTeXBasics of LaTeX
Basics of LaTeX
 
High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...
High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...
High Performance TensorFlow in Production -- Sydney ML / AI Train Workshop @ ...
 
Webinar: DevOps - Redefining your IT Strategy
Webinar: DevOps - Redefining your IT StrategyWebinar: DevOps - Redefining your IT Strategy
Webinar: DevOps - Redefining your IT Strategy
 

More from Taegyun Jeon

TensorFlow-KR 3rd meetup - Lightning Talk for SI Analytics
TensorFlow-KR 3rd meetup - Lightning Talk for SI AnalyticsTensorFlow-KR 3rd meetup - Lightning Talk for SI Analytics
TensorFlow-KR 3rd meetup - Lightning Talk for SI AnalyticsTaegyun Jeon
 
TensorFlow Dev Summit 2018 Extended: TensorFlow Eager Execution
TensorFlow Dev Summit 2018 Extended: TensorFlow Eager ExecutionTensorFlow Dev Summit 2018 Extended: TensorFlow Eager Execution
TensorFlow Dev Summit 2018 Extended: TensorFlow Eager ExecutionTaegyun Jeon
 
[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution
[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution
[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-ResolutionTaegyun Jeon
 
[PR12] PR-063: Peephole predicting network performance before training
[PR12] PR-063: Peephole predicting network performance before training[PR12] PR-063: Peephole predicting network performance before training
[PR12] PR-063: Peephole predicting network performance before trainingTaegyun Jeon
 
GDG DevFest Xiamen 2017
GDG DevFest Xiamen 2017GDG DevFest Xiamen 2017
GDG DevFest Xiamen 2017Taegyun Jeon
 
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...Taegyun Jeon
 
GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...
GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...
GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...Taegyun Jeon
 
[PR12] PR-036 Learning to Remember Rare Events
[PR12] PR-036 Learning to Remember Rare Events[PR12] PR-036 Learning to Remember Rare Events
[PR12] PR-036 Learning to Remember Rare EventsTaegyun Jeon
 
[대전AI포럼] 위성영상 분석 기술 개발 현황 소개
[대전AI포럼] 위성영상 분석 기술 개발 현황 소개[대전AI포럼] 위성영상 분석 기술 개발 현황 소개
[대전AI포럼] 위성영상 분석 기술 개발 현황 소개Taegyun Jeon
 
[PR12] PR-026: Notes for CVPR Machine Learning Sessions
[PR12] PR-026: Notes for CVPR Machine Learning Sessions[PR12] PR-026: Notes for CVPR Machine Learning Sessions
[PR12] PR-026: Notes for CVPR Machine Learning SessionsTaegyun Jeon
 
[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection
[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection
[PR12] You Only Look Once (YOLO): Unified Real-Time Object DetectionTaegyun Jeon
 
[PR12] image super resolution using deep convolutional networks
[PR12] image super resolution using deep convolutional networks[PR12] image super resolution using deep convolutional networks
[PR12] image super resolution using deep convolutional networksTaegyun Jeon
 
TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)
TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)
TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)Taegyun Jeon
 
인공지능: 변화와 능력개발
인공지능: 변화와 능력개발인공지능: 변화와 능력개발
인공지능: 변화와 능력개발Taegyun Jeon
 

More from Taegyun Jeon (14)

TensorFlow-KR 3rd meetup - Lightning Talk for SI Analytics
TensorFlow-KR 3rd meetup - Lightning Talk for SI AnalyticsTensorFlow-KR 3rd meetup - Lightning Talk for SI Analytics
TensorFlow-KR 3rd meetup - Lightning Talk for SI Analytics
 
TensorFlow Dev Summit 2018 Extended: TensorFlow Eager Execution
TensorFlow Dev Summit 2018 Extended: TensorFlow Eager ExecutionTensorFlow Dev Summit 2018 Extended: TensorFlow Eager Execution
TensorFlow Dev Summit 2018 Extended: TensorFlow Eager Execution
 
[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution
[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution
[OSGeo-KR Tech Workshop] Deep Learning for Single Image Super-Resolution
 
[PR12] PR-063: Peephole predicting network performance before training
[PR12] PR-063: Peephole predicting network performance before training[PR12] PR-063: Peephole predicting network performance before training
[PR12] PR-063: Peephole predicting network performance before training
 
GDG DevFest Xiamen 2017
GDG DevFest Xiamen 2017GDG DevFest Xiamen 2017
GDG DevFest Xiamen 2017
 
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...
[PR12] PR-050: Convolutional LSTM Network: A Machine Learning Approach for Pr...
 
GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...
GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...
GDG DevFest Seoul 2017: Codelab - Time Series Analysis for Kaggle using Tenso...
 
[PR12] PR-036 Learning to Remember Rare Events
[PR12] PR-036 Learning to Remember Rare Events[PR12] PR-036 Learning to Remember Rare Events
[PR12] PR-036 Learning to Remember Rare Events
 
[대전AI포럼] 위성영상 분석 기술 개발 현황 소개
[대전AI포럼] 위성영상 분석 기술 개발 현황 소개[대전AI포럼] 위성영상 분석 기술 개발 현황 소개
[대전AI포럼] 위성영상 분석 기술 개발 현황 소개
 
[PR12] PR-026: Notes for CVPR Machine Learning Sessions
[PR12] PR-026: Notes for CVPR Machine Learning Sessions[PR12] PR-026: Notes for CVPR Machine Learning Sessions
[PR12] PR-026: Notes for CVPR Machine Learning Sessions
 
[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection
[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection
[PR12] You Only Look Once (YOLO): Unified Real-Time Object Detection
 
[PR12] image super resolution using deep convolutional networks
[PR12] image super resolution using deep convolutional networks[PR12] image super resolution using deep convolutional networks
[PR12] image super resolution using deep convolutional networks
 
TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)
TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)
TensorFlow KR 2nd Meetup - Lightening talk (Satrec Initiative)
 
인공지능: 변화와 능력개발
인공지능: 변화와 능력개발인공지능: 변화와 능력개발
인공지능: 변화와 능력개발
 

Recently uploaded

Basic Principle of Electrochemical Sensor
Basic Principle of  Electrochemical SensorBasic Principle of  Electrochemical Sensor
Basic Principle of Electrochemical SensorTanvir Moin
 
Technology Features of Apollo HDD Machine, Its Technical Specification with C...
Technology Features of Apollo HDD Machine, Its Technical Specification with C...Technology Features of Apollo HDD Machine, Its Technical Specification with C...
Technology Features of Apollo HDD Machine, Its Technical Specification with C...Apollo Techno Industries Pvt Ltd
 
Landsman converter for power factor improvement
Landsman converter for power factor improvementLandsman converter for power factor improvement
Landsman converter for power factor improvementVijayMuni2
 
Clutches and brkesSelect any 3 position random motion out of real world and d...
Clutches and brkesSelect any 3 position random motion out of real world and d...Clutches and brkesSelect any 3 position random motion out of real world and d...
Clutches and brkesSelect any 3 position random motion out of real world and d...sahb78428
 
SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....
SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....
SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....santhyamuthu1
 
Graphics Primitives and CG Display Devices
Graphics Primitives and CG Display DevicesGraphics Primitives and CG Display Devices
Graphics Primitives and CG Display DevicesDIPIKA83
 
Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...
Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...
Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...Sean Meyn
 
Summer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdf
Summer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdfSummer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdf
Summer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdfNaveenVerma126
 
Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...
Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...
Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...amrabdallah9
 
Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...
Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...
Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...Amil baba
 
Transforming Process Safety Management: Challenges, Benefits, and Transition ...
Transforming Process Safety Management: Challenges, Benefits, and Transition ...Transforming Process Safety Management: Challenges, Benefits, and Transition ...
Transforming Process Safety Management: Challenges, Benefits, and Transition ...soginsider
 
Mohs Scale of Hardness, Hardness Scale.pptx
Mohs Scale of Hardness, Hardness Scale.pptxMohs Scale of Hardness, Hardness Scale.pptx
Mohs Scale of Hardness, Hardness Scale.pptxKISHAN KUMAR
 
Test of Significance of Large Samples for Mean = µ.pptx
Test of Significance of Large Samples for Mean = µ.pptxTest of Significance of Large Samples for Mean = µ.pptx
Test of Significance of Large Samples for Mean = µ.pptxHome
 
Phase noise transfer functions.pptx
Phase noise transfer      functions.pptxPhase noise transfer      functions.pptx
Phase noise transfer functions.pptxSaiGouthamSunkara
 
Design of Clutches and Brakes in Design of Machine Elements.pptx
Design of Clutches and Brakes in Design of Machine Elements.pptxDesign of Clutches and Brakes in Design of Machine Elements.pptx
Design of Clutches and Brakes in Design of Machine Elements.pptxYogeshKumarKJMIT
 
UNIT4_ESD_wfffffggggggggggggith_ARM.pptx
UNIT4_ESD_wfffffggggggggggggith_ARM.pptxUNIT4_ESD_wfffffggggggggggggith_ARM.pptx
UNIT4_ESD_wfffffggggggggggggith_ARM.pptxrealme6igamerr
 

Recently uploaded (20)

Basic Principle of Electrochemical Sensor
Basic Principle of  Electrochemical SensorBasic Principle of  Electrochemical Sensor
Basic Principle of Electrochemical Sensor
 
Technology Features of Apollo HDD Machine, Its Technical Specification with C...
Technology Features of Apollo HDD Machine, Its Technical Specification with C...Technology Features of Apollo HDD Machine, Its Technical Specification with C...
Technology Features of Apollo HDD Machine, Its Technical Specification with C...
 
計劃趕得上變化
計劃趕得上變化計劃趕得上變化
計劃趕得上變化
 
Landsman converter for power factor improvement
Landsman converter for power factor improvementLandsman converter for power factor improvement
Landsman converter for power factor improvement
 
Clutches and brkesSelect any 3 position random motion out of real world and d...
Clutches and brkesSelect any 3 position random motion out of real world and d...Clutches and brkesSelect any 3 position random motion out of real world and d...
Clutches and brkesSelect any 3 position random motion out of real world and d...
 
Lecture 4 .pdf
Lecture 4                              .pdfLecture 4                              .pdf
Lecture 4 .pdf
 
SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....
SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....
SATELITE COMMUNICATION UNIT 1 CEC352 REGULATION 2021 PPT BASICS OF SATELITE ....
 
Graphics Primitives and CG Display Devices
Graphics Primitives and CG Display DevicesGraphics Primitives and CG Display Devices
Graphics Primitives and CG Display Devices
 
Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...
Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...
Quasi-Stochastic Approximation: Algorithm Design Principles with Applications...
 
Lecture 2 .pdf
Lecture 2                           .pdfLecture 2                           .pdf
Lecture 2 .pdf
 
Summer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdf
Summer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdfSummer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdf
Summer training report on BUILDING CONSTRUCTION for DIPLOMA Students.pdf
 
Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...
Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...
Strategies of Urban Morphologyfor Improving Outdoor Thermal Comfort and Susta...
 
Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...
Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...
Popular-NO1 Kala Jadu Expert Specialist In Germany Kala Jadu Expert Specialis...
 
Transforming Process Safety Management: Challenges, Benefits, and Transition ...
Transforming Process Safety Management: Challenges, Benefits, and Transition ...Transforming Process Safety Management: Challenges, Benefits, and Transition ...
Transforming Process Safety Management: Challenges, Benefits, and Transition ...
 
Mohs Scale of Hardness, Hardness Scale.pptx
Mohs Scale of Hardness, Hardness Scale.pptxMohs Scale of Hardness, Hardness Scale.pptx
Mohs Scale of Hardness, Hardness Scale.pptx
 
Test of Significance of Large Samples for Mean = µ.pptx
Test of Significance of Large Samples for Mean = µ.pptxTest of Significance of Large Samples for Mean = µ.pptx
Test of Significance of Large Samples for Mean = µ.pptx
 
Phase noise transfer functions.pptx
Phase noise transfer      functions.pptxPhase noise transfer      functions.pptx
Phase noise transfer functions.pptx
 
Design of Clutches and Brakes in Design of Machine Elements.pptx
Design of Clutches and Brakes in Design of Machine Elements.pptxDesign of Clutches and Brakes in Design of Machine Elements.pptx
Design of Clutches and Brakes in Design of Machine Elements.pptx
 
UNIT4_ESD_wfffffggggggggggggith_ARM.pptx
UNIT4_ESD_wfffffggggggggggggith_ARM.pptxUNIT4_ESD_wfffffggggggggggggith_ARM.pptx
UNIT4_ESD_wfffffggggggggggggith_ARM.pptx
 
Présentation IIRB 2024 Marine Cordonnier.pdf
Présentation IIRB 2024 Marine Cordonnier.pdfPrésentation IIRB 2024 Marine Cordonnier.pdf
Présentation IIRB 2024 Marine Cordonnier.pdf
 

Google Dev Summit Extended Seoul - TensorFlow: Tensorboard & Keras