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Revision as of 13:01, 2 July 2023
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 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
_____________________________________________________________________________________
- 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
- 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
Scikit Machine Learning Map
SAS
Notes
