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Google APAC Machine Learning Expert Day

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Google APAC Machine Learning Day 是 Google 今年三月初於新加坡 Google 辦公室針對機器學習所舉辦的兩天研討會活動,本次聚會將邀請前往參加該活動的 Evan Lin 及他的同事 Benjamin Chen 帶來他們的心得分享,內容包括:

Tensorflow Summit RECAP
Machine Learning Expert Day 所見所聞
分享一下 Linker Networks 如何使用 Tensorflow


https://gdg-taipei.kktix.cc/events/google-apac-machine-learning-day

Veröffentlicht in: Internet
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Google APAC Machine Learning Expert Day

  1. 1. Google APAC Machine Learning Expert Day Linkernetworks - Evan Lin / Benjamin Chen
  2. 2. ● Tensorflow Summit Recap ● Google APAC Machine Learning Expert Day ● Our lightening talk (Linker Neworks) Agenda
  3. 3. Who is Evan Lin ● Daily Work: ○ Linker Networks : Cloud Architect in ● Community: ○ Co-Organizer in Golang Taipei User Group ● Habit: ○ Project 52
  4. 4. Tensorflow Summit RECAP
  5. 5. Tensorflow Dev Summit 2017 link
  6. 6. Benjamin Chen Linker Networks Data Scientist Taiwan R User Group Officer benjamin0901@gmail.com
  7. 7. After 1.0.0 ● 1.0.0 ○ XLA ○ pip install tensorflow ○ JAVA API ● 1.1.0 ○ Keras 2.0-->tf.contrib.keras ■ tf.keras by TF 1.2 ○ tf.estimator
  8. 8. TensorFlow Wide & Deep Learning Wide Model Deep Model Memorization Generalization Revelance Diversity
  9. 9. Deep Model Generalization Diversity
  10. 10. Wide Model Memorization Relevance
  11. 11. Wide & Deep Model
  12. 12. Classify cucumbers with tensorflow
  13. 13. Classify cucumbers with tensorflow
  14. 14. Japanese Idol with DCGAN (link)
  15. 15. APAC Machine Learning Expert Day 1
  16. 16. Some Interesting Projects
  17. 17. Deep Learning in your flash drive (link)
  18. 18. Tensorflow example from zero to all (link)
  19. 19. Tensorflow What? (link)
  20. 20. Other lightning talks ● Context and attention extraction / modeling ● NLU and Cognitive Architectures ● [Linker Networks] When Kubernetes meets Tensorflow ● [Linker Networks] Running Distributed Tensorflow with Jupyter Notebook and Kubernetes ● [Linker Networks] Machine Intelligent Cluster
  21. 21. APAC Machine Learning Expert Day 2
  22. 22. Tensorflow intro with Codelab (link)
  23. 23. Google Cloud Codelab
  24. 24. Classify Manhattan
  25. 25. Classify MNIST images
  26. 26. Linker Networks When Kubernetes meets Tensorflow
  27. 27. Machine Intelligence Cluster: Use Tensorflow to improve Kubernetes● Goal: ○ Kubernetes with Machine Intelligence ● Role played by ML: ○ Maximize utilization ○ Risk mitigation ● Tools Used: ○ Tensorflow ○ Spark Streaming
  28. 28. Utilization Prediction - Product: Cluster of Machine Intelligence, CMI - Goals: - Predict CPU and memory trend - Auto-scaling - Algorithm: LSTM - Module: Keras - Trying to tune threshold
  29. 29. Back to Evan
  30. 30. Eliminate engineering bottlenecks in Machine Learning
  31. 31. Data Collect Probe & Sensor & Smart GW Vizualization Data Process Data Analysis & Machine Learning DC/OS Spark ML Tensorflow DC/OS Storage Cassandra Kafka (Queueing) Go/Akka (Connector) Spark (ETL/Streaming) D3.js Scikit Learn R Interactive Dashboard Jupyter Notebook Zeppelin ML Job Scheduler Chronos HPC (with GPU) server Storage SDNStorage SDN
  32. 32. Analytics Machine Intelligence Platform (AMIP) : Building deep learning platform on top of Kubernetes ● Goal: ○ Zero setup for Tensorflow (private/public cloud) ○ Migrate with Jupyter, TensorBoard and TensorServing ● Tools Used: ○ Kubernetes ○ Tensorflow
  33. 33. AMIP Architecture
  34. 34. Linker is hiring Cloud Platform Developer - Familiar with DCOS/K8S - Strong DevOps experience
  35. 35. Q&A

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