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AL-702 (B) · Advance Machine Learning/Official Syllabus

Advance Machine Learning (AL-702 (B)) - Official Syllabus (AL-702)

1
Unit 1

UNIT-1 :Introduction

  • Algorithms and Machine Learning
  • Introduction to algorithms
  • Tools to analyze algorithms
  • Algorithmic techniques :Divide and Conquer
  • examples Randomization Applications
2
Unit 2

UNIT- 2 : Algorithms

  • Graphs maps Map searching
  • Application of algorithms :stable marriages example
  • Dictionaries and hashing
  • search trees
  • Dynamic programming
3
Unit 3

UNIT-3 : Application to Personal Genomics

  • Linear Programming NP completeness
  • Introduction to personal Genomics
  • Massive Raw data in Genomics
  • Data science on Personal Genomes
  • Inter connectedness on Personal Genomes
  • Case studies
4
Unit 4

UNIT-4 : Machine Learning

  • Introduction
  • Classification Linear Classification
  • Ensemble Classifiers
  • Model Selection
  • Cross Validation
  • Holdout
5
Unit 5

UNIT-5 : Machine Learning Applications

  • Probabilistic modelling
  • Topic modelling
  • Probabilistic Inference
  • Application :prediction of preterm birth
  • Data description and preparation
  • Relationship between machine learning and statistics
6
Unit 6

== END OF UNITS==

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