Caffe / Caffe2 - Revision history

BPeat at 01:37, 27 April 2024

2024-04-27T01:37:52Z

BPeat at 02:36, 7 July 2023

2023-07-07T02:36:16Z

BPeat at 02:36, 7 July 2023

2023-07-07T02:36:00Z

BPeat at 11:04, 4 July 2023

2023-07-04T11:04:57Z

BPeat at 20:03, 3 July 2023

2023-07-03T20:03:57Z

BPeat: Text replacement - "http:" to "https:"

2023-03-28T09:16:12Z

Text replacement - "http:" to "https:"

BPeat at 18:01, 17 March 2023

2023-03-17T18:01:35Z

BPeat at 02:38, 9 February 2023

2023-02-09T02:38:37Z

BPeat at 17:58, 25 August 2020

2020-08-25T17:58:48Z

BPeat at 03:00, 23 February 2019

2019-02-23T03:00:54Z

@@ Line 18: / Line 18: @@
 * [[Libraries & Frameworks Overview]] ... [[Libraries & Frameworks]] ... [[Git - GitHub and GitLab]] ... [[Other Coding options]]
-* [[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]]
 Deep-learning framework Caffe is “made with expression, speed, and modularity in mind.” Originally developed in 2013 for machine vision projects, Caffe has since expanded to include other applications, such as speech and multimedia. Speed is a major priority, so Caffe has been written entirely in C++, with CUDA acceleration support, although it can switch between CPU and GPU processing as needed. The distribution includes a set of free and open source reference models for common classification jobs, with other models created and donated by the Caffe user community.  A new iteration of Caffe backed by [[Meta|Facebook]], called Caffe2, is currently under [[development]] for a 1.0 release. Its goals are to make it easier to perform distributed training and deploy to mobile devices, to provide support for new kinds of hardware like FPGAs, and to make use of cutting-edge features like 16-bit floating-point training. [https://www.infoworld.com/article/3026262/machine-learning/13-frameworks-for-mastering-machine-learning.html 13 frameworks for mastering machine learning | Serdar Yegulalp]

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 [https://www.google.com/search?q=caffe2+caffe+deep+machine+learning+ML+artificial+intelligence ...Google search]
 * [[Libraries & Frameworks Overview]] ... [[Libraries & Frameworks]] ... [[Git - GitHub and GitLab]] ... [[Other Coding options]]
 * [[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]]

@@ Line 18: / Line 18: @@
 * [[Libraries & Frameworks Overview]]
-* [[Libraries & Frameworks]]
+* [[Libraries & Frameworks Overview]] ... [[Libraries & Frameworks]] ... [[Git - GitHub and GitLab]] ... [[Other Coding options]]
 * [[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]]

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 * [[Libraries & Frameworks Overview]]
 * [[Libraries & Frameworks]]
 Deep-learning framework Caffe is “made with expression, speed, and modularity in mind.” Originally developed in 2013 for machine vision projects, Caffe has since expanded to include other applications, such as speech and multimedia. Speed is a major priority, so Caffe has been written entirely in C++, with CUDA acceleration support, although it can switch between CPU and GPU processing as needed. The distribution includes a set of free and open source reference models for common classification jobs, with other models created and donated by the Caffe user community.  A new iteration of Caffe backed by [[Meta|Facebook]], called Caffe2, is currently under [[development]] for a 1.0 release. Its goals are to make it easier to perform distributed training and deploy to mobile devices, to provide support for new kinds of hardware like FPGAs, and to make use of cutting-edge features like 16-bit floating-point training. [https://www.infoworld.com/article/3026262/machine-learning/13-frameworks-for-mastering-machine-learning.html 13 frameworks for mastering machine learning | Serdar Yegulalp]

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 |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=caffe2+caffe+artificial+intelligence+deep+learning Youtube search...]

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 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
-[http://www.youtube.com/results?search_query=caffe2+caffe+artificial+intelligence+deep+learning Youtube search...]
+[https://www.youtube.com/results?search_query=caffe2+caffe+artificial+intelligence+deep+learning Youtube search...]
-[http://www.google.com/search?q=caffe2+caffe+deep+machine+learning+ML+artificial+intelligence ...Google search]
+[https://www.google.com/search?q=caffe2+caffe+deep+machine+learning+ML+artificial+intelligence ...Google search]
 * [[Libraries & Frameworks Overview]]
 * [[Libraries & Frameworks]]
-Deep-learning framework Caffe is “made with expression, speed, and modularity in mind.” Originally developed in 2013 for machine vision projects, Caffe has since expanded to include other applications, such as speech and multimedia. Speed is a major priority, so Caffe has been written entirely in C++, with CUDA acceleration support, although it can switch between CPU and GPU processing as needed. The distribution includes a set of free and open source reference models for common classification jobs, with other models created and donated by the Caffe user community.  A new iteration of Caffe backed by [[Meta|Facebook]], called Caffe2, is currently under [[development]] for a 1.0 release. Its goals are to make it easier to perform distributed training and deploy to mobile devices, to provide support for new kinds of hardware like FPGAs, and to make use of cutting-edge features like 16-bit floating-point training. [http://www.infoworld.com/article/3026262/machine-learning/13-frameworks-for-mastering-machine-learning.html 13 frameworks for mastering machine learning | Serdar Yegulalp]
+Deep-learning framework Caffe is “made with expression, speed, and modularity in mind.” Originally developed in 2013 for machine vision projects, Caffe has since expanded to include other applications, such as speech and multimedia. Speed is a major priority, so Caffe has been written entirely in C++, with CUDA acceleration support, although it can switch between CPU and GPU processing as needed. The distribution includes a set of free and open source reference models for common classification jobs, with other models created and donated by the Caffe user community.  A new iteration of Caffe backed by [[Meta|Facebook]], called Caffe2, is currently under [[development]] for a 1.0 release. Its goals are to make it easier to perform distributed training and deploy to mobile devices, to provide support for new kinds of hardware like FPGAs, and to make use of cutting-edge features like 16-bit floating-point training. [https://www.infoworld.com/article/3026262/machine-learning/13-frameworks-for-mastering-machine-learning.html 13 frameworks for mastering machine learning | Serdar Yegulalp]
 <youtube>rvMVqPsXL10</youtube>
 <youtube>-lYWSTE7nsY</youtube>
 <youtube>bOIZ74rOik0</youtube>

← Older revision		Revision as of 03:00, 23 February 2019
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	[http://www.google.com/search?q=caffe2+caffe+deep+machine+learning+ML+artificial+intelligence ...Google search]		[http://www.google.com/search?q=caffe2+caffe+deep+machine+learning+ML+artificial+intelligence ...Google search]

		+	* [[Libraries & Frameworks Overview]]
	* [[Libraries & Frameworks]]		* [[Libraries & Frameworks]]