Distributed Tensorflow on Kubernetes – Organized by SFBay ACM & ValleyML.ai

*** NO RSVP on MEETUP, ***
*** MUST PURCHASE TICKET on EVENTBRIGHT, click this link:
https://www.eventbrite.com/e/distributed-tensorflow-with-kubernetes-ai-workshop-by-sfbay-acm-tickets-58548919394?aff=meetup

One-day, 8-hr Bootcamp, during which you will have deep learning introduction to getting to production with optimized deployment.

Tickets:
$150 – Early Bird Registration [until 4/15/2019]
Group rate available: ($130 / person, Contact us for signing-up.)

We are seeking TA’s who know ML to help the audience. TA applicants should contact the instructors in advance. Use the [contact] button on the left, send email, phone, LinkedIn and ML experience).

TARGET AUDIENCE would include people who …
• are comfortable in programming
• may already work on consulting projects or in some technical business problem solving role.
• It is helpful if you have tried Python, Spark and BigDL before.

Topics covered by Bhairav Mehta:

-Introduction to Kubernetes
-Kubernetes Architecture
-Deploy an app to Kubernetes Cluster
-Expose App, Scale App And Update App in Kubernetes
-Managing State with Deployments
-Federations, Auditing and Debugging Kubernetes, Security Best Practices
-An introduction to TensorFlow on Kubernetes
-Introduction to distributed TensorFlow on Kubernetes
-The benefits of EFS for TensorFlow (image data storage for TensorFlow jobs)
-Pipeline uses the Kuberflor framework to deploy
-A JupyterHub to create & manage interactive Jupyter notebooks
-A TensorFlow Training Controller that can be configured to use CPUs or GPUs
-A TensorFlow Serving container

BEFORE THE CLASS, PREPARATIONS:
• For fun, play around with some neural nets at the TensorFlow Playground (http://playground.tensorflow.org). This will be covered in the class as well.

• PRE-LOADING:
For all workshops we will use Jupiter notebooks with Python, Spark and BigDL.

Notebook instances will be provided by the organizers.

• You are invited to submit a description of your upcoming machine learning projects or vertical. The instructor will review and may try to incorporate some ideas in the class. Through the meetup site, on the left margin, use the [contact] button.

SCHEDULE

8:30 arrive, register, coffee, network
9:00 – 10:00 lecture / lab
15 min break, coffee
10:15 – 11:30 lecture / lab
45 min break for lunch
12:15 -1:45 lecture / lab
15 min break, coffee, small snacks
2:00 – 3:30 lecture / lab
15 min break, coffee, small snacks
3:45 – 5:30 lab/ Q&A

ABOUT the Instructor:

Bhairav Mehta is Senior Data Scientist for Apple Inc. as Sr. Data Scientist. He is experienced engineer, business professional with 19 years of combined progressive experience working on data science in electronics consumer products industry (7 years at Apple Inc.), yield engineering in semiconductor manufacturing (6 years at Qualcomm and MIT Startup) and quality engineering in automotive industry (OEM, Tier2 Suppliers, Ford Motor Company) (3 years). Bhairav founded DataInquest Inc. in 2014 specialized in training/consulting in AI, Machine Learning, Blockchain and Data Science. Bhairav Mehta has MBA from Johnson School of Management at Cornell University, Masters in Computer science (Georgia Tech), Statistics (Cornell University}, and Industrial Systems Engineering (Rochester Institute of Technology).

Sunil Sabat has years of hardware and software industry skills in varieties of roles – Intel circuit design automation to delivering end to end enterprise software solutions (on-premise and cloud ) involving IBM, Oracle, Microsoft , AWS ( Amazon Web Services ), Google Cloud and Open Source technologies. Sunil has worked in various roles of product strategy, design, development, release, marketing, sales and support spanning over the entire revenue life cycle management backed up by direct business partner and customer engagement.