From d07098d3bf793ab30221c8d3a7ee87d7d57124ed Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 15:25:30 -0500 Subject: [PATCH 1/9] Update README.md to include link/links to GenAI tutorials --- tutorials/README.md | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/tutorials/README.md b/tutorials/README.md index e9cdb3f..25f6f0c 100644 --- a/tutorials/README.md +++ b/tutorials/README.md @@ -38,9 +38,7 @@ You can find a nice tutorial for using managed notebooks [here](https://codelabs ## **Artificial Intelligence and Machine Learning** Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed. Machine learning on GCP generally occurs within VertexAI. You can learn more about machine learning on GCP at this [Google Crash Course](https://developers.google.com/machine-learning/crash-course). For hands-on examples, try out [this module](https://github.com/NIGMS/COVIDMachineLearningSFSU) developed by San Francisco State University or [this one from the University of Arkasas](https://github.com/NIGMS/MachineLearningUA) developed for the NIGMS Sandbox Project. -Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capabile of are extracting wanted information from text, transforming speech into text, generating images from describtions and vice versa, and much more. Vertex AI's [Generative AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. You are also able to use these models within a jupyter notebook and Google provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). - -We created [this tutorial](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb) that uses [langchain with Vertex AI](https://python.langchain.com/docs/integrations/llms/google_vertex_ai_palm) to walk you through various Gen AI use cases, including programmatically querying a LLM, creating a custom chatbox that queries a scientific article about menopause in :monkey: (sorry no emoji for chimps), and generates code according to a user-specified prompt. +Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capabile of are extracting wanted information from text, transforming speech into text, generating images from describtions and vice versa, and much more. Vertex AI's [Generative AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over [Gemini](/tutorials/notebooks/GenAI/Gemini_intro.ipynb), [RAG](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb), [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb), [training via Huggingface](/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb), and more! The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). ## **Medical Image Segmentation** Medical image analysis is the application of computational algorithms and techniques to extract meaningful information from medical images for diagnosis, treatment planning, and research purposes. Medical image analysis requires large image files and often elastic storage and accelerated computing. From 766f42c1b0ada802b105614534cda5ea4efba976 Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 15:35:44 -0500 Subject: [PATCH 2/9] Update README.md fixed links --- tutorials/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/README.md b/tutorials/README.md index 25f6f0c..fb32ed5 100644 --- a/tutorials/README.md +++ b/tutorials/README.md @@ -38,7 +38,7 @@ You can find a nice tutorial for using managed notebooks [here](https://codelabs ## **Artificial Intelligence and Machine Learning** Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed. Machine learning on GCP generally occurs within VertexAI. You can learn more about machine learning on GCP at this [Google Crash Course](https://developers.google.com/machine-learning/crash-course). For hands-on examples, try out [this module](https://github.com/NIGMS/COVIDMachineLearningSFSU) developed by San Francisco State University or [this one from the University of Arkasas](https://github.com/NIGMS/MachineLearningUA) developed for the NIGMS Sandbox Project. -Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capabile of are extracting wanted information from text, transforming speech into text, generating images from describtions and vice versa, and much more. Vertex AI's [Generative AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over [Gemini](/tutorials/notebooks/GenAI/Gemini_intro.ipynb), [RAG](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb), [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb), [training via Huggingface](/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb), and more! The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). +Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capabile of are extracting wanted information from text, transforming speech into text, generating images from describtions and vice versa, and much more. Vertex AI's [Vertex AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over [Gemini](/tutorials/notebooks/GenAI/Gemini_Intro.ipynb), [RAG](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb), [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb), [training via Huggingface](/tutorials/notebooks/GenAI/GCP_GenAI_Huggingface.ipynb), and more! The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). ## **Medical Image Segmentation** Medical image analysis is the application of computational algorithms and techniques to extract meaningful information from medical images for diagnosis, treatment planning, and research purposes. Medical image analysis requires large image files and often elastic storage and accelerated computing. From 4c6e7f487c44a9014d1f1e5601fb3f694480be6a Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 15:37:38 -0500 Subject: [PATCH 3/9] Update and rename GenAIStudioGCP.ipynb to VertexAIStudioGCP.ipynb --- .../GenAI/{GenAIStudioGCP.ipynb => VertexAIStudioGCP.ipynb} | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename tutorials/notebooks/GenAI/{GenAIStudioGCP.ipynb => VertexAIStudioGCP.ipynb} (99%) diff --git a/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb b/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb similarity index 99% rename from tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb rename to tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb index b43803b..779b7e8 100644 --- a/tutorials/notebooks/GenAI/GenAIStudioGCP.ipynb +++ b/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb @@ -6,7 +6,7 @@ "id": "Hny4I-ODTIS6" }, "source": [ - "# Generative AI Studio on GCP - Article Summary\n" + "# VAI Studio on GCP - Article Summary\n" ] }, { From 9044f03bf677d62a8ddb5c840afd825c4551ecac Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 15:47:04 -0500 Subject: [PATCH 4/9] fixed spelling mistakes --- tutorials/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/README.md b/tutorials/README.md index fb32ed5..d065c06 100644 --- a/tutorials/README.md +++ b/tutorials/README.md @@ -38,7 +38,7 @@ You can find a nice tutorial for using managed notebooks [here](https://codelabs ## **Artificial Intelligence and Machine Learning** Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed. Machine learning on GCP generally occurs within VertexAI. You can learn more about machine learning on GCP at this [Google Crash Course](https://developers.google.com/machine-learning/crash-course). For hands-on examples, try out [this module](https://github.com/NIGMS/COVIDMachineLearningSFSU) developed by San Francisco State University or [this one from the University of Arkasas](https://github.com/NIGMS/MachineLearningUA) developed for the NIGMS Sandbox Project. -Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capabile of are extracting wanted information from text, transforming speech into text, generating images from describtions and vice versa, and much more. Vertex AI's [Vertex AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over [Gemini](/tutorials/notebooks/GenAI/Gemini_Intro.ipynb), [RAG](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb), [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb), [training via Huggingface](/tutorials/notebooks/GenAI/GCP_GenAI_Huggingface.ipynb), and more! The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). +Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capable of are extracting wanted information from text, transforming speech into text, generating images from descriptions and vice versa, and much more. Vertex AI's [Vertex AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over [Gemini](/tutorials/notebooks/GenAI/Gemini_Intro.ipynb), [RAG](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb), [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb), [training via Huggingface](/tutorials/notebooks/GenAI/GCP_GenAI_Huggingface.ipynb), and more! The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). ## **Medical Image Segmentation** Medical image analysis is the application of computational algorithms and techniques to extract meaningful information from medical images for diagnosis, treatment planning, and research purposes. Medical image analysis requires large image files and often elastic storage and accelerated computing. From 8e81bf6e62ecc6a69f9387b28898a814f43706aa Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 16:33:17 -0500 Subject: [PATCH 5/9] Update GCP_Pubmed_chatbot.ipynb add links to inference example scripts --- tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb b/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb index 7a3e657..6179d86 100644 --- a/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb +++ b/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb @@ -1010,7 +1010,7 @@ "id": "1abcbd48-bb84-4310-b8eb-ad87850a8649", "metadata": {}, "source": [ - "Running our script in the terminal will require us to export the following global variables before using the command `python NAME_OF_SCRIPT.py`." + "Running our script in the terminal will require us to export the following global variables before using the command `python NAME_OF_SCRIPT.py. You can also check out our example inference scripts for the [Pubmed API](/example_scripts/example_langchain_chat_llama_2_zeroshot.py) and [Vertex AI Vector Search](/example_scripts/example_vectorsearch_chat_llama_2_zeroshot)`." ] }, { From 9997753cc35d2939e74f776981f450cfe6cdafc6 Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 16:34:07 -0500 Subject: [PATCH 6/9] Update GCP_Pubmed_chatbot.ipynb_v2 --- tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb b/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb index 6179d86..4282e0d 100644 --- a/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb +++ b/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb @@ -1010,7 +1010,7 @@ "id": "1abcbd48-bb84-4310-b8eb-ad87850a8649", "metadata": {}, "source": [ - "Running our script in the terminal will require us to export the following global variables before using the command `python NAME_OF_SCRIPT.py. You can also check out our example inference scripts for the [Pubmed API](/example_scripts/example_langchain_chat_llama_2_zeroshot.py) and [Vertex AI Vector Search](/example_scripts/example_vectorsearch_chat_llama_2_zeroshot)`." + "Running our script in the terminal will require us to export the following global variables before using the command `python NAME_OF_SCRIPT.py`. You can also check out our example inference scripts for the [Pubmed API](/example_scripts/example_langchain_chat_llama_2_zeroshot.py) and [Vertex AI Vector Search](/example_scripts/example_vectorsearch_chat_llama_2_zeroshot)." ] }, { From 1226ee768de12278235ccfad77c3ddfdf59cab30 Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Wed, 17 Jan 2024 16:35:26 -0500 Subject: [PATCH 7/9] Update GCP_Pubmed_chatbot.ipynb fixing links --- tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb b/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb index 4282e0d..9798d2c 100644 --- a/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb +++ b/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb @@ -1010,7 +1010,7 @@ "id": "1abcbd48-bb84-4310-b8eb-ad87850a8649", "metadata": {}, "source": [ - "Running our script in the terminal will require us to export the following global variables before using the command `python NAME_OF_SCRIPT.py`. You can also check out our example inference scripts for the [Pubmed API](/example_scripts/example_langchain_chat_llama_2_zeroshot.py) and [Vertex AI Vector Search](/example_scripts/example_vectorsearch_chat_llama_2_zeroshot)." + "Running our script in the terminal will require us to export the following global variables before using the command `python NAME_OF_SCRIPT.py`. You can also check out our **example inference scripts** for the [Pubmed API](/example_scripts/example_langchain_chat_llama_2_zeroshot.py) and [Vertex AI Vector Search](/example_scripts/example_vectorsearch_chat_llama_2_zeroshot.py)." ] }, { From ca0f8dfe787e49a6e7bbd84872bceae8212c6551 Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Fri, 19 Jan 2024 08:58:14 -0500 Subject: [PATCH 8/9] Update README.md v3 --- tutorials/README.md | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/tutorials/README.md b/tutorials/README.md index d065c06..9d4a898 100644 --- a/tutorials/README.md +++ b/tutorials/README.md @@ -38,7 +38,9 @@ You can find a nice tutorial for using managed notebooks [here](https://codelabs ## **Artificial Intelligence and Machine Learning** Machine learning is a subfield of artificial intelligence that focuses on the development of algorithms and models that enable computers to learn from and make predictions or decisions based on data, without being explicitly programmed. Machine learning on GCP generally occurs within VertexAI. You can learn more about machine learning on GCP at this [Google Crash Course](https://developers.google.com/machine-learning/crash-course). For hands-on examples, try out [this module](https://github.com/NIGMS/COVIDMachineLearningSFSU) developed by San Francisco State University or [this one from the University of Arkasas](https://github.com/NIGMS/MachineLearningUA) developed for the NIGMS Sandbox Project. -Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capable of are extracting wanted information from text, transforming speech into text, generating images from descriptions and vice versa, and much more. Vertex AI's [Vertex AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting. See our overview in [this tutorial](/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over [Gemini](/tutorials/notebooks/GenAI/Gemini_Intro.ipynb), [RAG](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb), [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb), [training via Huggingface](/tutorials/notebooks/GenAI/GCP_GenAI_Huggingface.ipynb), and more! The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). +Now that the age of **Generative AI** (Gen AI) has arrived, Google has released a host of Gen AI offerings within the Vertex AI suite. Some examples of what generative AI models are capable of are extracting wanted information from text, transforming speech into text, generating images from descriptions and vice versa, and much more. Vertex AI's [Vertex AI Studio](https://cloud.google.com/vertex-ai/docs/generative-ai/learn/generative-ai-studio) console allows the user to rapidly create, test, and train generative AI models on the cloud in a safe and secure setting, see our overview in [this tutorial](/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb). The studio also has ready-to-use models all contained with in the [Model Garden](https://cloud.google.com/vertex-ai/docs/start/explore-models). These models range from foundation models, fine-tunable models, and task-specific solutions. +- To learn more about Gen AI on GCP take a look at our [GenAI tutorials](/tutorials/notebooks/GenAI) that go over several GCP products such as [Gemini](/tutorials/notebooks/GenAI/Gemini_Intro.ipynb) and [Vector Search](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb) and other tools like [Langchain](/tutorials/notebooks/GenAI/langchain_on_vertex.ipynb) and [Huggingface](/tutorials/notebooks/GenAI/GCP_GenAI_Huggingface.ipynb) to deploy, train, prompt, and implement techniques like [Retrieval-Augmented Generation (RAG)](/tutorials/notebooks/GenAI/GCP_Pubmed_chatbot.ipynb) to GenAI models. +- The Google github also provides many generative AI tutorials hosted on [GitHub](https://github.com/GoogleCloudPlatform/generative-ai/tree/main). Some example they provide are under [language here](https://github.com/GoogleCloudPlatform/generative-ai/tree/main/language). ## **Medical Image Segmentation** Medical image analysis is the application of computational algorithms and techniques to extract meaningful information from medical images for diagnosis, treatment planning, and research purposes. Medical image analysis requires large image files and often elastic storage and accelerated computing. From cac4e41750780360d02d4bb198683314ff058eb8 Mon Sep 17 00:00:00 2001 From: zbyosufzai <145053952+zbyosufzai@users.noreply.github.com> Date: Fri, 19 Jan 2024 10:46:31 -0500 Subject: [PATCH 9/9] fixed spelling --- tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb b/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb index 779b7e8..3366fff 100644 --- a/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb +++ b/tutorials/notebooks/GenAI/VertexAIStudioGCP.ipynb @@ -6,7 +6,7 @@ "id": "Hny4I-ODTIS6" }, "source": [ - "# VAI Studio on GCP - Article Summary\n" + "# Vertex AI Studio on GCP - Article Summary\n" ] }, {