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!
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!
Developers, DevOps, Data Scientists
- 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
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.