Difference between revisions of "AI Solver"
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| + | * [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Train, Validate, and Test]] | ||
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<i>Aids in selecting a starting algorithm for your solution; at that point discover similar algorithms to see which works best for your task (and data) at hand.</i> | <i>Aids in selecting a starting algorithm for your solution; at that point discover similar algorithms to see which works best for your task (and data) at hand.</i> | ||
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Lets get going? I want to... | Lets get going? I want to... | ||
| − | * ...detect patterns... | + | * ...detect patterns or relationships ... [[Causation vs. Correlation|Correlation analysis]] or [[Forecasting|Time series analysis]] |
** [[...predict values]]/quantity/outcomes | ** [[...predict values]]/quantity/outcomes | ||
** [[...predict categories]] so I can classify each data point into a specific groups | ** [[...predict categories]] so I can classify each data point into a specific groups | ||
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* ...find a [[Generative AI]]-type solution to identify the most plausible theory among competing explanations | * ...find a [[Generative AI]]-type solution to identify the most plausible theory among competing explanations | ||
** [https://hbr.org/2023/03/a-framework-for-picking-the-right-generative-ai-project A Framework for Picking the Right Generative AI Project | A Framework for Picking the Right Generative AI Project | M. Zao-Sanders & M. Ramos - Harvard Business Review] | ** [https://hbr.org/2023/03/a-framework-for-picking-the-right-generative-ai-project A Framework for Picking the Right Generative AI Project | A Framework for Picking the Right Generative AI Project | M. Zao-Sanders & M. Ramos - Harvard Business Review] | ||
| − | * ... automate processes; understand (semantic parsing) complete sentences, understanding synonyms of matching words, | + | * ... automate processes; understand (semantic parsing) complete sentences, understanding synonyms of matching words, [[Sentiment Analysis]], or [[Speech Recognition]], (speech) translation ...[[Natural Language Processing (NLP)]] |
| − | * ... [[Reinforcement Learning (RL) |pathfinding]]; learn a series of actions; find the best/shortest route to an objective; win a game, traveling salesman problem | + | * ... [[Reinforcement Learning (RL) |pathfinding]]; learn a series of actions; find the best/shortest route to an objective; win a game, traveling salesman problem ... [[Q Learning]], [[Deep Q Network (DQN)]] |
| + | * ... train [[Assistants]], [[Personal Companions]], or [[Agents]] | ||
_____________________________________________________________________________________ | _____________________________________________________________________________________ | ||
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* [[Algorithms]] & Neural Network Models to learn about approaches used to solve specific AI-related problems | * [[Algorithms]] & Neural Network Models to learn about approaches used to solve specific AI-related problems | ||
* [[Model Search]] | * [[Model Search]] | ||
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* [https://www.kdnuggets.com/2020/05/guide-choose-right-machine-learning-algorithm.html An easy guide to choose the right Machine Learning algorithm | Yogita Kinha - KDnuggets] | * [https://www.kdnuggets.com/2020/05/guide-choose-right-machine-learning-algorithm.html An easy guide to choose the right Machine Learning algorithm | Yogita Kinha - KDnuggets] | ||
* [https://dataconomy.com/2023/04/best-ai-models-types-how-to-choose-what-is/ Everything you should know about AI models | Eray Eliaçık - Dataconomy] | * [https://dataconomy.com/2023/04/best-ai-models-types-how-to-choose-what-is/ Everything you should know about AI models | Eray Eliaçık - Dataconomy] | ||
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https://cdn-images-1.medium.com/max/600/1*iPIGiJIcQjzZheEgTzOnhA.png | https://cdn-images-1.medium.com/max/600/1*iPIGiJIcQjzZheEgTzOnhA.png | ||
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*[https://docs.microsoft.com/en-us/azure/machine-learning/studio/algorithm-choice How to choose algorithms for Microsoft Azure Machine Learning | Microsoft] | *[https://docs.microsoft.com/en-us/azure/machine-learning/studio/algorithm-choice How to choose algorithms for Microsoft Azure Machine Learning | Microsoft] | ||
*[https://docs.microsoft.com/en-us/azure/machine-learning/studio/studio-overview-diagram Overview diagram of Azure Machine Learning Studio capabilities | Microsoft] | *[https://docs.microsoft.com/en-us/azure/machine-learning/studio/studio-overview-diagram Overview diagram of Azure Machine Learning Studio capabilities | Microsoft] | ||
| + | * [https://huggingface.co/models Models | Hugging Face] ... click on Sort: Trending | ||
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<img src="https://docs.microsoft.com/en-us/azure/machine-learning/studio/media/studio-overview-diagram/ml_studio_overview_v1.1.png" width="1225" height="900"> | <img src="https://docs.microsoft.com/en-us/azure/machine-learning/studio/media/studio-overview-diagram/ml_studio_overview_v1.1.png" width="1225" height="900"> | ||
Latest revision as of 07:00, 6 March 2024
- AI Solver ... Algorithms ... Administration ... Model Search ... Discriminative vs. Generative ... Train, Validate, and Test
Aids in selecting a starting algorithm for your solution; at that point discover similar algorithms to see which works best for your task (and data) at hand.
Lets get going? I want to...
- ...detect patterns or relationships ... Correlation analysis or Time series analysis
- ...predict values/quantity/outcomes
- ...predict categories so I can classify each data point into a specific groups
- ...cluster data points to discover relationships and structure; find hidden structure
- ...make a Recommendation
- ...identify the most important features (attributes) or perform Dimensional Reduction
- ...find outliers; unusual points, anomaly detection
- ...find a Generative AI-type solution to identify the most plausible theory among competing explanations
- ... automate processes; understand (semantic parsing) complete sentences, understanding synonyms of matching words, Sentiment Analysis, or Speech Recognition, (speech) translation ...Natural Language Processing (NLP)
- ... pathfinding; learn a series of actions; find the best/shortest route to an objective; win a game, traveling salesman problem ... Q Learning, Deep Q Network (DQN)
- ... train Assistants, Personal Companions, or Agents
_____________________________________________________________________________________
- Algorithms & Neural Network Models to learn about approaches used to solve specific AI-related problems
- Model Search
- How to pick an algorithm | Willem Meints
- Model Mindmap | Mindmeister
- An easy guide to choose the right Machine Learning algorithm | Yogita Kinha - KDnuggets
- Everything you should know about AI models | Eray Eliaçık - Dataconomy
Microsoft Azure Studio Cheatsheet
- How to choose algorithms for Microsoft Azure Machine Learning | Microsoft
- Overview diagram of Azure Machine Learning Studio capabilities | Microsoft
- Models | Hugging Face ... click on Sort: Trending
Scikit Machine Learning Map
SAS
Notes
