ITC Analytics Accelerator: Difference between revisions
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* Prediction: process of using a model that is yet to happen | * Prediction: process of using a model that is yet to happen | ||
=== Flexibility vs Interpretability of models=== | === Flexibility vs Interpretability of models=== | ||
* Flexibility: capture a wide range of phenomena (Data fit) | |||
* Interpretability : Design a Pattern to facilitate the decision | |||
=== Regression vs classification=== | === Regression vs classification=== | ||
Revision as of 13:10, 12 October 2023
OVERVIEW
5i: Ideation: defining Intelligence: process of prediciton Inception: model building Intervention: Developing a segment Independance: Live DATA ENGINEERING collection Sructuring Cleaning ALGORITHUMS Classification & Regression Decision Tree Tree based Algorithums (RF model Ensemble models MODEL PERFORMANCE Model selection AI & ML ML supervised Unsupervised DEEP LEARNING Reinforment learning CNN IMPLEMENTATION of ADVANCED ANALTICS Tracking CHANGE MANAGEMENT Piller & Practics
Advanced Analytics
Value of AA
- Evolution: Excel > Storage > Tableu > Alerts > predicting the future > ML >
- Applications:
- Descriptive (historical. advanced statistics) >
- Predictive (Future. Uses ML. detection of fraud) >
- Prescriptive (influence the future. Data driven decision making); Optimization;
Five concepts
Statistical Learning
- Frame of understanding the data based on statistics
- Eg: L.Regression: Used in predictive analytics
- Linear model: regression or classification
Inference vs prediction
- Inference : process of evaluating the relationship of predictor and the response
- Prediction: process of using a model that is yet to happen
Flexibility vs Interpretability of models
- Flexibility: capture a wide range of phenomena (Data fit)
- Interpretability : Design a Pattern to facilitate the decision