Visualization

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• Tools:
  • Visualization with Python
  • Google: People + AI Research (PAIR)
    • TensorBoard
    • Neural Networks Playground
    • Facets
  • 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
  • D3.js
  • React-vis
  • Chart.js
  • VX
  • Recharts
• 5 Python Libraries for Creating Interactive Plots | Melissa Bierly | Mode
  • mpld
  • Pygal
  • Bokeh
  • HoloViews
  • Plotly
• 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
  • PowerBI
  • Tableau Public
  • QlikSense
  • Dundas BI
  • Infogram
  • Google Charts
  • Looker
  • Paraview (open source)
  • Excel
  • Oracle Analytics Cloud
  • IBM Cognos Analytics
  • ThoughtSpot
  • Apache Spark
  • Sisense
  • Talend
  • Salesforce Einstein Analytics
  • SAS Viya
• 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