Difference between revisions of "AI Solver"
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| Line 11: | Line 11: | ||
* ...detect patterns... | * ...detect patterns... | ||
| − | ** [[...predict values]]/quantity | + | ** [[...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 | ||
| − | ** [[...cluster]] data points to discover relationships and structure | + | ** [[...cluster]] data points to discover relationships and structure; find hidden structure |
** ...make a [[Recommendation]] | ** ...make a [[Recommendation]] | ||
* ...identify the most important features (attributes) or perform [[Dimensional Reduction]] | * ...identify the most important features (attributes) or perform [[Dimensional Reduction]] | ||
| Line 19: | Line 19: | ||
* ...find a [[Generative]]-type solution to identify the most plausible theory among competing explanations | * ...find a [[Generative]]-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)]] | * ... 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]]; 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 |
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Revision as of 18:28, 2 October 2019
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...
- ...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-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
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- Capabilities
- 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
Microsoft Azure Studio Cheatsheet
- How to choose algorithms for Microsoft Azure Machine Learning | Microsoft
- Overview diagram of Azure Machine Learning Studio capabilities | Microsoft
Scikit Machine Learning Map
SAS
Notes
