From 459466258d565c6134b96d6bff8837cc53f94797 Mon Sep 17 00:00:00 2001 From: GitHub Actions Date: Thu, 7 Nov 2024 14:40:00 +0000 Subject: [PATCH] site deploy Auto-generated via `{sandpaper}` Source : daafb215c4b1748014a7d7acb82ac767e9490ed8 Branch : md-outputs Author : GitHub Actions Time : 2024-11-07 14:39:46 +0000 Message : markdown source builds Auto-generated via `{sandpaper}` Source : 5ab43b47f7de68c45d73caceb166547c2da2801e Branch : main Author : Chris Endemann Time : 2024-11-07 14:38:59 +0000 Message : Update Training-models-in-SageMaker-notebooks.md --- Training-models-in-SageMaker-notebooks.html | 21 ++++++++++++------- aio.html | 20 +++++++++++------- ...raining-models-in-SageMaker-notebooks.html | 21 ++++++++++++------- instructor/aio.html | 20 +++++++++++------- md5sum.txt | 2 +- pkgdown.yml | 2 +- 6 files changed, 56 insertions(+), 30 deletions(-) diff --git a/Training-models-in-SageMaker-notebooks.html b/Training-models-in-SageMaker-notebooks.html index effde78..503f770 100644 --- a/Training-models-in-SageMaker-notebooks.html +++ b/Training-models-in-SageMaker-notebooks.html @@ -1337,10 +1337,13 @@

How SageMaker Expected training time: Training on a single instance takes prohibitively long (e.g., >10 hours), and distributed computing overhead is manageable. - +
+
+
-
-

Cost of distributed computing

+
+

Cost of distributed computing

+

tl;dr Use 1 instance unless you are finding that you’re waiting hours for the training/tuning to complete.

Let’s break down some key points for deciding between 1 @@ -1403,7 +1406,10 @@

Cost of distributed computingCost of distributed computingXGBoost’s distributed training mechanism

In the event that option 2 explained above really is better for your use-case (e.g., you have a very large dataset or model that takes a @@ -1495,14 +1502,14 @@

4. Final model aggregation significant time savings as dataset sizes and computational requirements increase. Here’s how you can configure it:

  1. -Select Multiple Instances: Specify +Select multiple instances: Specify instance_count > 1 in the SageMaker Estimator to enable distributed training.
  2. -Optimize Instance Type: Choose an instance type +Optimize instance type: Choose an instance type suitable for your dataset size and XGBoost requirements
  3. -Monitor for Speed Improvements: With larger +Monitor for speed improvements: With larger datasets, distributed training can yield time savings by scaling horizontally. However, gains may vary depending on the dataset and computation per instance.
    4. diff --git a/aio.html b/aio.html index ec5c591..d86867b 100644 --- a/aio.html +++ b/aio.html @@ -3372,11 +3372,13 @@

    How SageMaker instance takes prohibitively long (e.g., >10 hours), and distributed computing overhead is manageable. +
    +
    +
    -
    -
    -

    Cost of distributed computing -

    +
    +

    Cost of distributed computing

    +

    tl;dr Use 1 instance unless you are finding that you’re waiting hours for the training/tuning to complete.

    Let’s break down some key points for deciding between 1 @@ -3453,6 +3455,9 @@

    Cost of distributed computingCost of distributed computingXGBoost’s distributed training mechanism

    @@ -3563,14 +3569,14 @@

    4. Final model aggregation increase. Here’s how you can configure it:

    1. -Select Multiple Instances: Specify +Select multiple instances: Specify instance_count > 1 in the SageMaker Estimator to enable distributed training.
    2. -Optimize Instance Type: Choose an instance type +Optimize instance type: Choose an instance type suitable for your dataset size and XGBoost requirements
    3. -Monitor for Speed Improvements: With larger +Monitor for speed improvements: With larger datasets, distributed training can yield time savings by scaling horizontally. However, gains may vary depending on the dataset and computation per instance.
      4. diff --git a/instructor/Training-models-in-SageMaker-notebooks.html b/instructor/Training-models-in-SageMaker-notebooks.html index 83cae21..b6ded3d 100644 --- a/instructor/Training-models-in-SageMaker-notebooks.html +++ b/instructor/Training-models-in-SageMaker-notebooks.html @@ -1339,10 +1339,13 @@

      How SageMaker Expected training time: Training on a single instance takes prohibitively long (e.g., >10 hours), and distributed computing overhead is manageable. -

    +
    +
    +
    -
    -

    Cost of distributed computing

    +
    +

    Cost of distributed computing

    +

    tl;dr Use 1 instance unless you are finding that you’re waiting hours for the training/tuning to complete.

    Let’s break down some key points for deciding between 1 @@ -1405,7 +1408,10 @@

    Cost of distributed computingCost of distributed computingXGBoost’s distributed training mechanism

    In the event that option 2 explained above really is better for your use-case (e.g., you have a very large dataset or model that takes a @@ -1497,14 +1504,14 @@

    4. Final model aggregation significant time savings as dataset sizes and computational requirements increase. Here’s how you can configure it:

    1. -Select Multiple Instances: Specify +Select multiple instances: Specify instance_count > 1 in the SageMaker Estimator to enable distributed training.
    2. -Optimize Instance Type: Choose an instance type +Optimize instance type: Choose an instance type suitable for your dataset size and XGBoost requirements
    3. -Monitor for Speed Improvements: With larger +Monitor for speed improvements: With larger datasets, distributed training can yield time savings by scaling horizontally. However, gains may vary depending on the dataset and computation per instance.
      4. diff --git a/instructor/aio.html b/instructor/aio.html index a544c8f..1631ef4 100644 --- a/instructor/aio.html +++ b/instructor/aio.html @@ -3380,11 +3380,13 @@

      How SageMaker instance takes prohibitively long (e.g., >10 hours), and distributed computing overhead is manageable. +
      +
      +
      -
      -
      -

      Cost of distributed computing -

      +
      +

      Cost of distributed computing

      +

      tl;dr Use 1 instance unless you are finding that you’re waiting hours for the training/tuning to complete.

      Let’s break down some key points for deciding between 1 @@ -3461,6 +3463,9 @@

      Cost of distributed computingCost of distributed computingXGBoost’s distributed training mechanism

      @@ -3571,14 +3577,14 @@

      4. Final model aggregation increase. Here’s how you can configure it:

      1. -Select Multiple Instances: Specify +Select multiple instances: Specify instance_count > 1 in the SageMaker Estimator to enable distributed training.
      2. -Optimize Instance Type: Choose an instance type +Optimize instance type: Choose an instance type suitable for your dataset size and XGBoost requirements
      3. -Monitor for Speed Improvements: With larger +Monitor for speed improvements: With larger datasets, distributed training can yield time savings by scaling horizontally. However, gains may vary depending on the dataset and computation per instance.
        4. diff --git a/md5sum.txt b/md5sum.txt index 659f41d..0cb8f66 100644 --- a/md5sum.txt +++ b/md5sum.txt @@ -9,7 +9,7 @@ "episodes/SageMaker-notebooks-as-controllers.md" "7b44f533d49559aa691b8ab2574b4e81" "site/built/SageMaker-notebooks-as-controllers.md" "2024-11-06" "episodes/Accessing-S3-via-SageMaker-notebooks.md" "6f7c3a395851fe00f63e7eb44e553830" "site/built/Accessing-S3-via-SageMaker-notebooks.md" "2024-11-06" "episodes/Interacting-with-code-repo.md" "105dace64e3a1ea6570d314e4b3ccfff" "site/built/Interacting-with-code-repo.md" "2024-11-06" -"episodes/Training-models-in-SageMaker-notebooks.md" "ace4f0313d2edc5564b6bbf3d46335f3" "site/built/Training-models-in-SageMaker-notebooks.md" "2024-11-07" +"episodes/Training-models-in-SageMaker-notebooks.md" "df102099945f116048ff948364a2ec0a" "site/built/Training-models-in-SageMaker-notebooks.md" "2024-11-07" "episodes/Training-models-in-SageMaker-notebooks-part2.md" "a508320d07314a39d83b9b4c8114e92b" "site/built/Training-models-in-SageMaker-notebooks-part2.md" "2024-11-07" "episodes/Hyperparameter-tuning.md" "c9fe9c20d437dc2f88315438ac6460db" "site/built/Hyperparameter-tuning.md" "2024-11-07" "instructors/instructor-notes.md" "cae72b6712578d74a49fea7513099f8c" "site/built/instructor-notes.md" "2023-03-16" diff --git a/pkgdown.yml b/pkgdown.yml index 73bb95c..1dd6e94 100644 --- a/pkgdown.yml +++ b/pkgdown.yml @@ -2,4 +2,4 @@ pandoc: 3.1.11 pkgdown: 2.1.1 pkgdown_sha: ~ articles: {} -last_built: 2024-11-07T14:34Z +last_built: 2024-11-07T14:39Z