From 0278462a757bc6dcbac63d052f34ba4b249db0f1 Mon Sep 17 00:00:00 2001 From: GitHub Actions Date: Tue, 28 Nov 2023 06:09:16 +0000 Subject: [PATCH] markdown source builds Auto-generated via {sandpaper} Source : 6b091be4e0636306c570d1db83cd52437ef653ac Branch : main Author : Vlad Dracula Time : 2023-11-28 06:07:55 +0000 Message : copy edit link to previous episode for gridsearch --- 05-evaluate-predict-cnn.md | 2 +- md5sum.txt | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/05-evaluate-predict-cnn.md b/05-evaluate-predict-cnn.md index 5caf8f79..baf8869c 100644 --- a/05-evaluate-predict-cnn.md +++ b/05-evaluate-predict-cnn.md @@ -344,7 +344,7 @@ For instance, suppose you're tuning two hyperparameters: ## Tune Optimizer using Grid Search -In [Episode 04](./04-fit-cnn.md) we talked briefly about the `Adam` optimizer used in our `model.compile` discussion. Recall the optimizer refers to the algorithm with which the model learns to optimize on the provided loss function. +In [Episode 04 Compile and Train a Convolutional Neural Network](episodes/04-fit-cnn.md) we talked briefly about the `Adam` optimizer used in our `model.compile` discussion. Recall the optimizer refers to the algorithm with which the model learns to optimize on the provided loss function. Here we will use our introductory model to demonstrate how GridSearch is expressed in code to search for an optimizer. diff --git a/md5sum.txt b/md5sum.txt index d5977960..f30a84cb 100644 --- a/md5sum.txt +++ b/md5sum.txt @@ -9,7 +9,7 @@ "episodes/02-image-data.md" "0ca9bc92b9bf83e54d48787faa681f3d" "site/built/02-image-data.md" "2023-11-28" "episodes/03-build-cnn.md" "06e0475df3f110651bde9662144e1732" "site/built/03-build-cnn.md" "2023-11-22" "episodes/04-fit-cnn.md" "50dedd6b106f690a24e9495e1c2a93b9" "site/built/04-fit-cnn.md" "2023-11-23" -"episodes/05-evaluate-predict-cnn.md" "b2a1d8d4c1ee2400b665b80f47e3fcd0" "site/built/05-evaluate-predict-cnn.md" "2023-11-23" +"episodes/05-evaluate-predict-cnn.md" "20f0c5027bf430f277422b38736e1195" "site/built/05-evaluate-predict-cnn.md" "2023-11-28" "episodes/06-conclusion.md" "c62de2055655448aba58501325967415" "site/built/06-conclusion.md" "2023-10-11" "instructors/instructor-notes.md" "cae72b6712578d74a49fea7513099f8c" "site/built/instructor-notes.md" "2023-08-22" "learners/reference.md" "1c7cc4e229304d9806a13f69ca1b8ba4" "site/built/reference.md" "2023-09-25"