AWS Workshop: TensorFlow in SageMaker! 🔶👩‍🏫

This awesome 𝘛𝘦𝘯𝘴𝘰𝘳𝘍𝘭𝘰𝘸 𝘪𝘯 𝘚𝘢𝘨𝘦𝘔𝘢𝘬𝘦𝘳 hands-on workshop is hosted by AWS, conducted by an Amazon specialist ML solutions architect and with mentoring by Amazon solution architects! 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗹𝗶𝗻𝗸 𝗯𝗲𝗹𝗼𝘄 𝗶𝘀 𝗳𝗿𝗲𝗲 𝗯𝘂𝘁 𝗺𝗮𝗻𝗱𝗮𝘁𝗼𝗿𝘆!

𝗡𝗼𝘁𝗲: This is a hands-on session. Bring your own laptop and work with us! Basic Python and ML knowledge is required.

𝗔𝗴𝗲𝗻𝗱𝗮:
🍕 17:00 - 17:20 - Gathering, registration, snacks & mingling
🔶 17:20 - 20:00 - Workshop! (𝘏𝘦𝘣𝘳𝘦𝘸)

𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: https://floor28.co.il/event/100d97c9-f264-4b05-9e49-da687316ee5c
𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗹𝗶𝗻𝗸 𝗶𝘀 𝗳𝗿𝗲𝗲 𝗯𝘂𝘁 𝗺𝗮𝗻𝗱𝗮𝘁𝗼𝗿𝘆!

𝗔𝗯𝘀𝘁𝗿𝗮𝗰𝘁: TensorFlow/Keras enables developers to quickly and easily get started with deep learning in the cloud. You can get started on AWS with a fully-managed TensorFlow/Keras experience with Amazon SageMaker, a platform to build, train, and deploy machine learning models at scale.

You can use Amazon SageMaker to train and deploy a model using custom TensorFlow code. The Amazon SageMaker Python SDK TensorFlow estimators and models and the Amazon SageMaker open-source TensorFlow containers make writing a TensorFlow script and running it in Amazon SageMaker easier.

In this workshop you will port a working TensorFlow script to run on SageMaker and utilize some of the feature available for TensorFlow in SageMaker.

We will go over:

1. Porting a TensorFlow script to run in SageMaker using SageMaker script mode.
2. Monitoring your training job using TensorBoard and Amazon CloudWatch metrics.
3. Optimizing your training job using SageMaker pipemode input.
4. Running a distributed training job.
5. Deploying your trained model on Amazon SageMaker.

𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻: https://floor28.co.il/event/100d97c9-f264-4b05-9e49-da687316ee5c
𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝘂𝘀𝗶𝗻𝗴 𝘁𝗵𝗲 𝗹𝗶𝗻𝗸 𝗶𝘀 𝗳𝗿𝗲𝗲 𝗯𝘂𝘁 𝗺𝗮𝗻𝗱𝗮𝘁𝗼𝗿𝘆!

𝗡𝗼𝘁𝗲: This is a hands-on session. Bring your own laptop and work with us! Basic Python and ML knowledge is required.