Difference between revisions of "Visualization"
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* [[Explainable Artificial Intelligence (XAI)]] | * [[Explainable Artificial Intelligence (XAI)]] | ||
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** [[Python#Visualization with Python |Visualization with Python]] | ** [[Python#Visualization with Python |Visualization with Python]] | ||
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* [[Graphical Tools for Modeling AI Components]] | * [[Graphical Tools for Modeling AI Components]] | ||
* [http://bookdown.org/max/FES/exploratory-visualizations.html Feature Engineering and Selection: A Practical Approach for Predictive Models - 4 Exploratory Visualizations | Max Kuhn and Kjell Johnson] | * [http://bookdown.org/max/FES/exploratory-visualizations.html Feature Engineering and Selection: A Practical Approach for Predictive Models - 4 Exploratory Visualizations | Max Kuhn and Kjell Johnson] | ||
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<youtube>wvsE8jm1GzE</youtube> | <youtube>wvsE8jm1GzE</youtube> | ||
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<youtube>Ok44otx90D4</youtube> | <youtube>Ok44otx90D4</youtube> | ||
| − | == <span id="Python"></span>[[Python#Visualization with Python| Visualization with Python]] | + | == <span id="Dimension Reduction"></span>Dimension Reduction == |
| + | * [[Principal Component Analysis (PCA)]] | ||
| + | * [[T-Distributed Stochastic Neighbor Embedding (t-SNE)]] ...similar objects are modeled by nearby points | ||
| + | * [http://arxiv.org/pdf/1802.03426.pdf Uniform Manifold Approximation and Projection (UMAP) | L. McInnes, J. Healy, and J. Melville] ... a dimension reduction technique that can be used for visualisation similarly to [[T-Distributed Stochastic Neighbor Embedding (t-SNE) | t-SNE]], but also for general non-linear dimension reduction. | ||
| + | ** [http://github.com/lmcinnes/umap UMAP]...[[Python]] version | ||
| + | ** [http://github.com/pair-code/umap-js UMAP-JS] ...[[Javascript]] version | ||
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| + | <youtube>YPJQydzTLwQ</youtube> | ||
| + | <youtube>4NlvatkpV3s</youtube> | ||
| + | <youtube>_1msVvPE_KY</youtube> | ||
| + | <youtube>nq6iPZVUxZU</youtube> | ||
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| + | = <span id="Python"></span>[[Python#Visualization with Python| Visualization with Python]] = | ||
<youtube>a9UrKTVEeZA</youtube> | <youtube>a9UrKTVEeZA</youtube> | ||
Revision as of 08:49, 21 August 2020
YouTube search... ...Google search
- Explainable Artificial Intelligence (XAI)
- Tools:
- Visualization with Python
- Google: People + AI Research (PAIR)
- TensorBoard
- TensorFlow Playground
- Facets
- Projector.TensorFlow.org] ...3D visualization of search queries
- Visualize Keras Models with One Line of Code | Lukas & Jeff - Weights & Biases
- Visual DL
- Netron
- Yellowbrick
- CNNVis
- 3D Visualization of a Convolutional Neural Network (CNN)
- ANN Visualizer
- displaCy
- The Five Best Data Visualization Libraries | Lio Fleishman, Sisense
- 5 Python Libraries for Creating Interactive Plots | Melissa Bierly | Mode
- The 9 Best Analytics Tools For Data Visualization Available Today and The 10 Best Data Analytics And BI Platforms And Tools In 2020 | Bernard Marr - Forbes
- 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
- A Gentle Introduction to Data Visualization Methods in Python | Jason Brownlee - Machine Learning Mastery
- Data Flow Graph (DFG)
- Explainable Artificial Intelligence (XAI)
- (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
- The Simpsons meets Data Visualization | Adam Reevesman -Towards Data Science
- 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
- Feature Exploration/Learning
- Graphical Tools for Modeling AI Components
- Feature Engineering and Selection: A Practical Approach for Predictive Models - 4 Exploratory Visualizations | Max Kuhn and Kjell Johnson
Dimension Reduction
- Principal Component Analysis (PCA)
- T-Distributed Stochastic Neighbor Embedding (t-SNE) ...similar objects are modeled by nearby points
- Uniform Manifold Approximation and Projection (UMAP) | L. McInnes, J. Healy, and J. Melville ... a dimension reduction technique that can be used for visualisation similarly to t-SNE, but also for general non-linear dimension reduction.
- UMAP...Python version
- UMAP-JS ...Javascript version
Visualization with Python
Shan Carter
