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Machine Learning Techniques

Description

  • To understand the need for machine learning for various problem solving
  • To study the various supervised, semi-supervised and unsupervised learning algorithms in machine learning
  • To learn the new approaches in machine learning
  • To design appropriate machine learning algorithms for problem solving

What Will I Learn?

  • Differentiate between supervised, unsupervised, semi-supervised machine learning approaches
  • Apply specific supervised or unsupervised machine learning algorithm for a particular problem
  • Analyse and suggest the appropriate machine learning approach for the various types of problem
  • Design and make modifications to existing machine learning algorithms to suit an individual application
  • Provide useful case studies on the advanced machine learning algorithms

Topics for this course

5 Lessons50h

MACHINE LEARNING TECHNIQUES

Lesson 1-MACHINE LEARNING TECHNIQUES
Lesson 2-NEURAL NETWORKS AND GENETIC ALGORITHMS
Lesson 3-BAYESIAN AND COMPUTATIONAL LEARNING
Lesson 4-ADVANCED LEARNING
Lesson 5-Functions

About the instructor

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518 Courses

2 students

Free

Material Includes

  • Ethem Alpaydin, ―Introduction to Machine Learning (Adaptive Computation and Machine Learning)‖, The MIT Press 2004.
  • Stephen Marsland, ―Machine Learning: An Algorithmic Perspective‖, CRC Press, 2009.

Requirements

  • B.E/Diploma Students Can Pursue this Course

Target Audience

  • All Engineering Students Can Participate