Difference between revisions of "Visualization"
| Line 23: | Line 23: | ||
* [http://www.evolvingai.org/files/2016-VelezClune-SRC.pdf Identifying core functional networks and functional modules within artificial neural networks via subsets regression | Velez R, Clune J], 2016 | * [http://www.evolvingai.org/files/2016-VelezClune-SRC.pdf Identifying core functional networks and functional modules within artificial neural networks via subsets regression | Velez R, Clune J], 2016 | ||
* [[3D Simulation Environments]] | * [[3D Simulation Environments]] | ||
| − | + | * [[Datasets]] | |
| + | * [[Batch Norm(alization) & Standardization]] | ||
| + | * [[Data Preprocessing & Feature Exploration/Learning]] | ||
| + | * [[Hyperparameters]] | ||
| + | * [[Data Augmentation]] | ||
| + | * [[Master Data Management (MDM) / Feature Store / Data Lineage / Data Catalog]] | ||
<youtube>ze08gwVPaXk</youtube> | <youtube>ze08gwVPaXk</youtube> | ||
Revision as of 12:27, 20 January 2019
YouTube search... ...Google search
- Tools:
- The Five Best Data Visualization Libraries | Lio Fleishman, Sisense
- Data Visualization for Artificial Intelligence, and Vice Versa | Nicolas Kruchten
- Overview of Model Visualization Architecture and Types | XenonStack
- Understanding ML/DL Models using Interactive Visualization Techniques | Chakri Cherukuri
- Explainable Artificial Intelligence (EAI)
- (Deep) Convolutional Neural Network (DCNN/CNN)
- Multifaceted feature visualization: Uncovering the different types of features learned by each neuron in deep neural networks. Visualization for Deep Learning workshop | Nguyen A, Yosinski J, Clune J, 2016
- Identifying core functional networks and functional modules within artificial neural networks via subsets regression | Velez R, Clune J, 2016
- 3D Simulation Environments
- Datasets
- Batch Norm(alization) & Standardization
- Data Preprocessing & Feature Exploration/Learning
- Hyperparameters
- Data Augmentation
- Master Data Management (MDM) / Feature Store / Data Lineage / Data Catalog
