Google APAC Machine Learning Expert Day

Linkernetworks - Evan Lin / Benjamin Chen

● Tensorflow Summit Recap ● Google APAC Machine Learning Expert Day● Our lightening talk (Linker Neworks)

Agenda

Who is Evan Lin

● Daily Work:

○ Linker Networks : Cloud

Architect in

● Community:

○ Co-Organizer in Golang

Taipei User Group

● Habit:

○ Project 52

Tensorflow Summit RECAP

Tensorflow Dev Summit 2017

link

Benjamin ChenLinker Networks

Data ScientistTaiwan R User Group

Officer

benjamin0901@gmail.com

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

TensorFlow Wide & Deep Learning

Wide Model Deep Model

Memorization Generalization

Revelance Diversity

Deep ModelGeneralization

Diversity

Wide ModelMemorization

Relevance

Wide & Deep Model

Classify cucumbers with tensorflow

Classify cucumbers with tensorflow

Japanese Idol with DCGAN (link)

APAC Machine Learning Expert Day 1

Some Interesting Projects

Deep Learning in your flash drive (link)

Tensorflow example from zero to all (link)

Tensorflow What? (link)

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

APAC Machine Learning Expert Day 2

Tensorflow intro with Codelab (link)

Google Cloud Codelab

Classify Manhattan

Classify MNIST images

Linker NetworksWhen Kubernetes meets Tensorflow

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

Utilization Prediction- Product: Cluster of Machine

Intelligence, CMI- Goals:

- Predict CPU and memory trend

- Auto-scaling

- Algorithm: LSTM- Module: Keras- Trying to tune threshold

Back to Evan

Eliminate engineering bottlenecks

in Machine Learning

Data Collect Probe & Sensor & Smart GW

Vizualization

Data Process

Data Analysis &Machine Learning DC/OS Spark ML Tensorflow

DC/OS

StorageCassandra

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

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

AMIP Architecture

Linker is hiringCloud Platform Developer

- Familiar with DCOS/K8S- Strong DevOps experience

Q&A