Vertex AI - Revision history

BPeat at 02:15, 27 April 2024

2024-04-27T02:15:16Z

BPeat at 11:59, 5 July 2023

2023-07-05T11:59:40Z

BPeat at 20:10, 9 May 2023

2023-05-09T20:10:17Z

BPeat at 19:47, 9 May 2023

2023-05-09T19:47:06Z

BPeat at 19:46, 9 May 2023

2023-05-09T19:46:21Z

BPeat at 19:44, 9 May 2023

2023-05-09T19:44:52Z

BPeat at 19:43, 9 May 2023

2023-05-09T19:43:11Z

BPeat at 19:42, 9 May 2023

2023-05-09T19:42:10Z

BPeat at 19:37, 9 May 2023

2023-05-09T19:37:10Z

BPeat at 19:31, 9 May 2023

2023-05-09T19:31:30Z

@@ Line 20: / Line 20: @@
 [https://www.bing.com/news/search?q=Vertex+AI+Google&qft=interval%3d%228%22 ...Bing News]
-* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless, Generators, Drag n' Drop]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
+* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
 * [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]

@@ Line 2: / Line 2: @@
 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [https://www.youtube.com/results?search_query=Vertex+AI+Google YouTube]
@@ Line 11: / Line 20: @@
 [https://www.bing.com/news/search?q=Vertex+AI+Google&qft=interval%3d%228%22 ...Bing News]
-* [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)]]
+* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless, Generators, Drag n' Drop]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
-** [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]
+* [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]
 Vertex AI is a [[Machine Learning (ML)]] platform that lets you train and deploy ML models and AI applications. Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset.

@@ Line 11: / Line 11: @@
 [https://www.bing.com/news/search?q=Vertex+AI+Google&qft=interval%3d%228%22 ...Bing News]
-* [[SageMaker]] ... [[Vertex AI]] ... [[Azure AI Platform]] ... [[Watsonx]]
+* [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)]]
-* [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]
+** [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]
 Vertex AI is a [[Machine Learning (ML)]] platform that lets you train and deploy ML models and AI applications. Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset.

@@ Line 11: / Line 11: @@
 [https://www.bing.com/news/search?q=Vertex+AI+Google&qft=interval%3d%228%22 ...Bing News]
-* [[SageMaker]] Studio ... [[Vertex AI]] ... [[Azure AI Platform]] ... [[Watsonx]]
+* [[SageMaker]] ... [[Vertex AI]] ... [[Azure AI Platform]] ... [[Watsonx]]
 * [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]

@@ Line 11: / Line 11: @@
 [https://www.bing.com/news/search?q=Vertex+AI+Google&qft=interval%3d%228%22 ...Bing News]
-* [[SageMaker]] Studio | [[Amazon]], [[Vertex AI]] | [[Google]] ... [[Azure AI Platform]] | [[Microsoft]] ... [[Watsonx]] | [[IBM]]
+* [[SageMaker]] Studio ... [[Vertex AI]] ... [[Azure AI Platform]] ... [[Watsonx]]
 * [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]

@@ Line 5: / Line 5: @@
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[https://www.youtube.com/results?search_query=sagemaker+aws+tutorial+deep+machine+learning+ML YouTube search...]
+[https://www.youtube.com/results?search_query=Vertex+AI+Google YouTube]
-[https://www.google.com/search?q=sagemaker+aws+tutorial+deep+machine+learning+ML ...Google search]
+[https://www.quora.com/search?q=%20Vertex%20AI%20Google ... Quora]
 * [[SageMaker]] Studio | [[Amazon]], [[Vertex AI]] | [[Google]] ... [[Azure AI Platform]] | [[Microsoft]] ... [[Watsonx]] | [[IBM]]

@@ Line 15: / Line 15: @@
 Vertex AI provides several options for model training:
-AutoML lets you train tabular, image, text, or video data without writing code or preparing data splits.
+* AutoML lets you train tabular, image, text, or video data without writing code or preparing data splits.
-Custom training gives you complete control over the training process, including using your preferred ML framework, writing your own training code, and choosing hyperparameter tuning options.
+* Custom training gives you complete control over the training process, including using your preferred ML framework, writing your own training code, and choosing hyperparameter tuning options.
 After you deploy your models, use Vertex AI's end-to-end MLOps tools to automate and scale projects throughout the ML lifecycle. These MLOps tools are run on fully-managed infrastructure that you can customize based on your performance and budget needs.

@@ Line 8: / Line 8: @@
 [https://www.google.com/search?q=sagemaker+aws+tutorial+deep+machine+learning+ML ...Google search]
-* [[SageMaker]] Studio | [[Amazon]], [[Vertex AI]] | [[Google]] ... [[Azure AI Platform]] | [[Microsoft]] ... Watsonx | [[IBM]]
+* [[SageMaker]] Studio | [[Amazon]], [[Vertex AI]] | [[Google]] ... [[Azure AI Platform]] | [[Microsoft]] ... [[Watsonx]] | [[IBM]]
-* [https://cloud.google.com/vertex-ai Vertex AI]
+* [https://cloud.google.com/vertex-ai Vertex AI] | [[Google]]
 Vertex AI is a machine learning (ML) platform that lets you train and deploy ML models and AI applications. Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset.
@@ Line 24: / Line 24: @@
 https://cloud.google.com/static/vertex-ai/docs/start/images/mlops.png

← Older revision		Revision as of 19:31, 9 May 2023
Line 9:		Line 9:

	* [[SageMaker]] Studio \| [[Amazon]], [[Vertex AI]] \| [[Google]] ... [[Azure AI Platform]] \| [[Microsoft]] ... Watsonx \| [[IBM]]		* [[SageMaker]] Studio \| [[Amazon]], [[Vertex AI]] \| [[Google]] ... [[Azure AI Platform]] \| [[Microsoft]] ... Watsonx \| [[IBM]]
		+	* [https://cloud.google.com/vertex-ai Vertex AI]
		+
		+	Vertex AI is a machine learning (ML) platform that lets you train and deploy ML models and AI applications. Vertex AI combines data engineering, data science, and ML engineering workflows, enabling your teams to collaborate using a common toolset.
		+
		+	Vertex AI provides several options for model training:
		+
		+	AutoML lets you train tabular, image, text, or video data without writing code or preparing data splits.
		+
		+	Custom training gives you complete control over the training process, including using your preferred ML framework, writing your own training code, and choosing hyperparameter tuning options.
		+
		+	After you deploy your models, use Vertex AI's end-to-end MLOps tools to automate and scale projects throughout the ML lifecycle. These MLOps tools are run on fully-managed infrastructure that you can customize based on your performance and budget needs.
		+
		+	You can use the Vertex AI SDK for Python to run the entire machine learning workflow in Vertex AI Workbench, a Jupyter notebook-based development environment. Other available interfaces include the Google Cloud Console, the gcloud command line tool, client libraries, and Terraform (limited support).
		+
		+	https://cloud.google.com/static/vertex-ai/docs/start/images/mlops.png