From 04fcd90c2780eb8beee7bf8f4c717a14936f124b Mon Sep 17 00:00:00 2001 From: Jan <116908874+jk4e@users.noreply.github.com> Date: Fri, 21 Mar 2025 22:50:25 +0100 Subject: [PATCH 1/2] Fix typo --- colabs/intro/Intro_to_Weights_&_Biases.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/colabs/intro/Intro_to_Weights_&_Biases.ipynb b/colabs/intro/Intro_to_Weights_&_Biases.ipynb index 0536c27c..c3cb13db 100644 --- a/colabs/intro/Intro_to_Weights_&_Biases.ipynb +++ b/colabs/intro/Intro_to_Weights_&_Biases.ipynb @@ -146,7 +146,7 @@ "source": [ "Now that we know how to integrate W&B into a psuedo machine learning training loop, let's track a machine learning experiment using a basic PyTorch neural network. The following code will also upload model checkpoints to W&B that you can then share with other teams in in your organization.\n", "\n", - "## Track a machine learning experiment using Pytorch\n", + "## Track a machine learning experiment using PyTorch\n", "\n", "The following code cell defines and trains a simple MNIST classifier. During training, you will see W&B prints out URLs. Click on the project page link to see your results stream in live to a W&B project.\n", "\n", @@ -224,7 +224,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Create a teble to compare the predicted values versus the true value\n", + "### Create a table to compare the predicted values versus the true value\n", "\n", "The following cell is unique to W&B, so let's go over it.\n", "\n", From 7027258600ec84f3f2cdbd5c84eade6cf34f2093 Mon Sep 17 00:00:00 2001 From: Jan <116908874+jk4e@users.noreply.github.com> Date: Mon, 24 Mar 2025 17:24:18 +0100 Subject: [PATCH 2/2] Fix typo --- colabs/intro/Intro_to_Weights_&_Biases.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/colabs/intro/Intro_to_Weights_&_Biases.ipynb b/colabs/intro/Intro_to_Weights_&_Biases.ipynb index c3cb13db..c9018404 100644 --- a/colabs/intro/Intro_to_Weights_&_Biases.ipynb +++ b/colabs/intro/Intro_to_Weights_&_Biases.ipynb @@ -144,7 +144,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Now that we know how to integrate W&B into a psuedo machine learning training loop, let's track a machine learning experiment using a basic PyTorch neural network. The following code will also upload model checkpoints to W&B that you can then share with other teams in in your organization.\n", + "Now that we know how to integrate W&B into a pseudo machine learning training loop, let's track a machine learning experiment using a basic PyTorch neural network. The following code will also upload model checkpoints to W&B that you can then share with other teams in in your organization.\n", "\n", "## Track a machine learning experiment using PyTorch\n", "\n",