Difference between revisions of "Visualization"
m |
m |
||
| Line 26: | Line 26: | ||
** [[Data Flow Graph (DFG)]] | ** [[Data Flow Graph (DFG)]] | ||
** [[Graphical Tools for Modeling AI Components]] | ** [[Graphical Tools for Modeling AI Components]] | ||
| + | * [https://towardsdatascience.com/the-simpsons-meets-data-visualization-ef8ef0819d13 The Simpsons meets Data Visualization | Adam Reevesman -Towards Data Science] | ||
| + | * [[Robotics]] ... [[Transportation (Autonomous Vehicles)|Vehicles]] ... [[Autonomous Drones|Drones]] ... [[3D Model]] ... [[Point Cloud]] | ||
| + | * [[Simulation]] ... [[Simulated Environment Learning]] ... [[Minecraft]]: [[Minecraft#Voyager|Voyager]] | ||
| + | * [[Data Science]] | ||
| + | ** [[Data Governance]] | ||
| + | *** [[Benchmarks]] | ||
| + | *** [[Data Preprocessing]] | ||
| + | **** [[Feature Exploration/Learning]] | ||
| + | **** [[Data Quality]] ...[[AI Verification and Validation|validity]], [[Evaluation - Measures#Accuracy|accuracy]], [[Data Quality#Data Cleaning|cleaning]], [[Data Quality#Data Completeness|completeness]], [[Data Quality#Data Consistency|consistency]], [[Data Quality#Data Encoding|encoding]], [[Data Quality#Zero Padding|padding]], [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|augmentation, labeling, auto-tagging]], [[Data Quality#Batch Norm(alization) & Standardization| normalization, standardization]], and [[Data Quality#Imbalanced Data|imbalanced data]] | ||
| + | *** [[Bias and Variances]] | ||
| + | *** [[Algorithm Administration#Master Data Management (MDM)|Master Data Management (MDM)]] | ||
| + | **** [[Natural Language Processing (NLP)#Managed Vocabularies |Managed Vocabularies]] | ||
| + | **** [[Datasets]] | ||
| + | *** [[Privacy]] in Data Science | ||
| + | *** [[Data Interoperability]] | ||
* Tools: | * Tools: | ||
** [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database|Database; Vector & Relational]] ... [[Graph]] ... [[LlamaIndex]] | ** [[Excel]] ... [[LangChain#Documents|Documents]] ... [[Database|Database; Vector & Relational]] ... [[Graph]] ... [[LlamaIndex]] | ||
| Line 81: | Line 96: | ||
* [https://www.evolvingai.org/files/mfv_icml_workshop_16.pdf 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 | * [https://www.evolvingai.org/files/mfv_icml_workshop_16.pdf 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 | ||
* [https://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 | * [https://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 | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
* [https://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] | * [https://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] | ||
Latest revision as of 08:20, 16 June 2024
YouTube ... Quora ...Google search ...Google News ...Bing News
- Analytics ... Visualization ... Graphical Tools ... Diagrams & Business Analysis ... Requirements ... Loop ... Bayes ... Network Pattern
- Hyperparameters
- Predictive Analytics ... Predictive Maintenance ... Forecasting ... Market Trading ... Sports Prediction ... Marketing ... Politics ... Excel
- Graph
- The Simpsons meets Data Visualization | Adam Reevesman -Towards Data Science
- Robotics ... Vehicles ... Drones ... 3D Model ... Point Cloud
- Simulation ... Simulated Environment Learning ... Minecraft: Voyager
- Data Science
- Tools:
- Excel ... Documents ... Database; Vector & Relational ... Graph ... LlamaIndex
- Visualization with Python
- Google: People + AI Research (PAIR)
- TensorBoard | Google
- TensorFlow Playground | Google
- Facets | Google
- Projector.TensorFlow.org] | Google ...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
- Virtualitics ... Get more from your data and your team with AI-powered data exploration ... from Descriptive to Prescriptive
- Artificial General Intelligence (AGI) to Singularity ... Curious Reasoning ... Emergence ... Moonshots ... Explainable AI ... Automated Learning
- (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
- Feature Engineering and Selection: A Practical Approach for Predictive Models - 4 Exploratory Visualizations | Max Kuhn and Kjell Johnson
Visualization with Python
Shan Carter
