JNTUH B.Tech 4th year (4-2) Predictive Analytics (Associate Analytics -III) gives you detail information of Predictive Analytics (Associate Analytics -III) (Elective -II) 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 Segmentation(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-Ill.
REFERENCE BOOK
- Gareth James’ Daniela Witten Trevor Hastie Robert Tibshirani. An Introduction to Statistical Learning with Applications in R
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