Difference between revisions of "Directed Acyclic Graph (DAG)"
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|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 | ||
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| − | [ | + | [https://www.youtube.com/results?search_query=Directed+Acyclic+Graph+DAG+pipeline+program+machine+learning YouTube search...] |
| − | [ | + | [https://www.google.com/search?q=Directed+Acyclic+Graph+DAG+pipeline+program+machine+learning ...Google search] |
| − | * [ | + | * [https://www.cv-foundation.org/openaccess/content_iccv_2015/papers/Yang_Multi-Scale_Recognition_With_ICCV_2015_paper.pdf Multi-scale recognition with DAG-CNNs | Songfan Yang & Deva Ramanan] |
| − | * [ | + | * [https://www.qubole.com/blog/the-key-to-building-data-pipelines-for-machine-learning-support-for-multiple-engines/ The Key to Building Data Pipelines for Machine Learning: Support for Multiple Engines | Jorge Villamariona - Qubole] |
| − | * [ | + | * [https://www.ebayinc.com/stories/blogs/tech/running-arbitrary-dag-based-workflows-in-the-cloud/ Running Arbitrary DAG-based Workflows in the Cloud | Sachin Tilloo] |
* [[Data Flow Graph (DFG)]] | * [[Data Flow Graph (DFG)]] | ||
* [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]] | * [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]] | ||
* [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)]] | * [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)]] | ||
| − | * [ | + | * [https://stats.stackexchange.com/questions/234694/can-all-neural-network-with-dag-topology-be-trained-by-back-prop Can all neural network having directed acyclic graph (DAG) topology be trained by back propagation methods? | StackExchange] |
| + | * [[Blockchain]] | ||
| − | A DAG network is a neural network for deep learning with layers arranged as a directed acyclic graph. A DAG network can have a more complex architecture in which layers have inputs from multiple layers and outputs to multiple layers. [ | + | A DAG network is a neural network for deep learning with layers arranged as a directed acyclic graph. A DAG network can have a more complex architecture in which layers have inputs from multiple layers and outputs to multiple layers. [https://www.mathworks.com/help/deeplearning/ref/dagnetwork.html DAGNetwork | MathWorks] |
| − | DAG workflow are set of tasks written with dependencies between the tasks rather than linearly chaining. [ | + | DAG workflow are set of tasks written with dependencies between the tasks rather than linearly chaining. [https://www.kdnuggets.com/2019/02/4-reasons-machine-learning-code-probably-bad.html 4 Reasons Why Your Machine Learning Code is Probably Bad - Norman Niemer - KDnuggets] |
| − | ** [ | + | ** [https://github.com/d6t/d6tflow/blob/master/docs/example-ml.md Example Usage For a Machine Learning Workflow | GitHub] |
| − | + | https://www.mathworks.com/help/examples/nnet/win64/CreateSimpleDAGNetworkExample_03.png | |
<youtube>LOr_abIZL04</youtube> | <youtube>LOr_abIZL04</youtube> | ||
Latest revision as of 09:08, 28 March 2023
YouTube search... ...Google search
- Multi-scale recognition with DAG-CNNs | Songfan Yang & Deva Ramanan
- The Key to Building Data Pipelines for Machine Learning: Support for Multiple Engines | Jorge Villamariona - Qubole
- Running Arbitrary DAG-based Workflows in the Cloud | Sachin Tilloo
- Data Flow Graph (DFG)
- Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning
- Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)
- Can all neural network having directed acyclic graph (DAG) topology be trained by back propagation methods? | StackExchange
- Blockchain
A DAG network is a neural network for deep learning with layers arranged as a directed acyclic graph. A DAG network can have a more complex architecture in which layers have inputs from multiple layers and outputs to multiple layers. DAGNetwork | MathWorks
DAG workflow are set of tasks written with dependencies between the tasks rather than linearly chaining. 4 Reasons Why Your Machine Learning Code is Probably Bad - Norman Niemer - KDnuggets
DAG Technology: 'DAG Coins' as an Alternative to Blockchain/Cryptocurrencies
