Machine Learning Engineering – Monitoring training (FREE)
Overview
This is part of Machine Learning Engineering and DevOps Learning Series.
Here we will focus on how to monitor training and be notified when training is done
This is a FREE Class!
On-Demand
Can’t make it to live session? No worries. Go ahead and register; we will send you the session recording .
See below for past session recordings & notes
What you will learn
- Using callbacks and TensorBoard to monitor training progress
- Set model to train until to a point (90% accuracy) using callbacks instead of fixed set # of epochs
- Send periodic summary statistics using Slack and/or Twilio
- Notify MLE when training is done!
Intended Audience
Developers, DevOps, Data Scientists
Prerequisites
- Must have : Development experience
- Nice to have: Python knowledge
What to Bring
- Please bring a reasonably modern laptop (Corporate laptops with overly restrictive firewalls may not work well; Personal laptops are recommended)
- Need to have a Machine Learning Environment setup on your laptop. Please follow this guide
- [nice to have] download our docker image elephantscale/es-training
Presenters
Sujee Maniyam
Sujee Maniyam is a seasoned practitioner and founder of Elephant Scale. He teaches and consults in AI (machine learning and deep learning) and Big Data (Hadoop, Spark, NoSQL) and and Cloud technologies.
He is an open source contributor, author ( ‘Hadoop illuminated‘ and ‘HBase Design Patterns‘) and speaker at conferences. He also advises and mentors various companies and organizations.
