School of Cyber Tech

Neural Networks

Rocheston Neural Networks course teaches you the advanced concepts and terminologies involved in creating an Artificial Neural Networks. The program explains the architecture and provides training the various algorithms used in ANN. The program is made up of a comprehensive set of modules that provide both an understanding and insight into developments in convolutional Neural Networks, Self-organizing Maps, Boltzmann machines, applications of artificial neural networks and auto encoders in practice.

Rocheston Neural Networks course teaches you the advanced concepts and terminologies involved in creating an Artificial Neural Networks. The program explains the architecture and provides training the various algorithms used in ANN. The program is...

There is no description for this course

Course content

  • Lesson Module 1: Introduction
  • Lesson Module 2: Basic Concepts
  • Lesson Module 3: Building Blocks
  • Lesson Module 4: Learning and Adaptation
  • Lesson Module 5: Supervised Learning
  • Lesson Module 6: Unsupervised Learning
  • Lesson Module 7: Learning Vector Quantization
  • Lesson Module 8: Adaptive Resonance Theory
  • Lesson Module 9: Kohonen Self - Organizing Feature
  • Lesson Module 10: Associative Memory Network
  • Lesson Module 11: Hopfield Networks
  • Lesson Module 12: Boltzmann Machine
  • Lesson Module 13: Brain-state-in-a-Box Network
  • Lesson Module 14: Optimization Using Hopfield
  • Lesson Module 15: Other Optimization Techniques
  • Lesson Module 16: Genetic Algorithm
  • Lesson Module 17: Applications of Neural Networks