From b704e2f8bfb8ad6519f0d83229c57e017a316b39 Mon Sep 17 00:00:00 2001 From: Petter Olsson Date: Sun, 17 Nov 2024 08:46:02 -0800 Subject: [PATCH] Fixed dataset location in a template based workshop Pushed from Domino: https://ykb.domino-eval.com/workspace/petter/mlops-best-practices?executionId=6734940e0b77b232dfd8c697 --- .ipynb_checkpoints/Readme-checkpoint.md | 8 ++++---- Readme.md | 2 +- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/.ipynb_checkpoints/Readme-checkpoint.md b/.ipynb_checkpoints/Readme-checkpoint.md index 034857b..c9192cd 100644 --- a/.ipynb_checkpoints/Readme-checkpoint.md +++ b/.ipynb_checkpoints/Readme-checkpoint.md @@ -1,14 +1,14 @@ # Domino Hands-On Workshop: Predictions -## Updated for Domino 6.x - #### In this workshop, you will work through an end-to-end workflow broken into various labs to - -* Read in data from a live source +* Read in data from a live datasource * Prepare your data in an IDE of your choice, with an option to leverage distributed computing clusters * Train several models in various frameworks * Compare model performance across different frameworks and select the best-performing model * Deploy model to a containerized endpoint and web-app frontend for consumption * Leverage collaboration and documentation capabilities to make all work reproducible and sharable! -You will find a full walkthrough of our Workshop here: [WORKSHOP LINK](https://docs.google.com/document/u/4/d/11eA3ney10KzX7GF9G7f5n72f4p7k7CHSpLxoUfbAGE8/pub) \ No newline at end of file +You will find a full walkthrough of our Workshop here: [VERSION 6.x WORKSHOP LINK](https://docs.google.com/document/u/4/d/11eA3ney10KzX7GF9G7f5n72f4p7k7CHSpLxoUfbAGE8/pub) + +You will find a full walkthrough of our Workshop here: [VERSION 5.x WORKSHOP LINK](https://docs.google.com/document/d/e/2PACX-1vS9LKbBYYOrsDmshmKvEIUkDMYVMAivoodg1CTEgjZRPW_IJFV2Un4l5uaE2jI1BsbN3-tQ8IMSkGoL/pub) \ No newline at end of file diff --git a/Readme.md b/Readme.md index 0a71b17..c9192cd 100644 --- a/Readme.md +++ b/Readme.md @@ -2,7 +2,7 @@ #### In this workshop, you will work through an end-to-end workflow broken into various labs to - -* Read in data from a live source +* Read in data from a live datasource * Prepare your data in an IDE of your choice, with an option to leverage distributed computing clusters * Train several models in various frameworks * Compare model performance across different frameworks and select the best-performing model