JNTUH B.Tech 4th year (4-2) Predictive Analytics (Associate Analytics – III) gives you detail information of Predictive Analytics (Associate Analytics – III) (Elective – III) R13 syllabus It will be help full to understand you complete curriculum of the year.
Unit – I
Introduction to Predictive Analytics & Linear Regression (NOS 2101): What and Why Analytics, Introduction to Tools and Environment, Application of Modelling in Business, Databases & Types of data and variables, Data Modelling Techniques, Missing imputations etc. Need for Business Modelling. Regression — Concepts, Blue property-assumptions-Least Square Estimation. Variable Rationalization, and Model Building etc.
Unit – II
Logistic Regression (NOS 2101): Model Theory, Model fit Statistics, Model Conclusion, Analytics applications to various Business Domains etc. Regression Vs Segmentation — Supervised and Unsupervised Learning, Tree Building — Regression, Classification, Overfitting, Pruning and complexity. Multiple Decision Trees etc.
Unit – III
Objective Segrnentation(NOS 2101): Regression Vs Segmentation — Supervised and Unsupervised Learning, Tree Building — Regression, Classification, Overfitting, Pruning and complexity, Multiple Decision Trees etc. Develop Knowledge, Skill and Competences (NOS 9005) Introduction to Knowledge skills & competences, Training & Development, Learning & Development, Policies and Record keeping, etc.
TEXT BOOK
- Student’s Handbook for Associate Analytics-III.
REFERENCE BOOK
Gareth James • Daniela Witten • Trevor Hastie Robert Tibshirani. An Introduction to Statistical Learning with Applications in R
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All the topics are not covered in handbook.
No refernce for the remaing topics!
HANDBOOK IS NOT SO RELEVANT..A CLEAR MATERIAL OR BOOK SHOULD BE PROVIDED
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