School of Cyber Tech

Deep Learning

Rocheston's Deep Learning course delves into the concepts and applications and the different kinds of Neural Networks for supervised and unsupervised learning. Deep Learning is a critical component of AI technologies that are developed across the globe. In this program, will learn to build complex models that will help machines to solve real-world problems with human-level intelligence. The program also covers advanced concepts of Deep Learning by building models and algorithms using libraries like Keras, PyTorch and Tensorflow.

Rocheston's Deep Learning course delves into the concepts and applications and the different kinds of Neural Networks for supervised and unsupervised learning. Deep Learning is a critical component of AI technologies that are developed across the ...

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Course content

  • Lesson Module 1: Introduction
  • Lesson Module 2: Machine Learning Basics
  • Lesson Module 3: Deep Feedforward Networks
  • Lesson Module 4: Regularization for Deep Learning
  • Lesson Module 5: Optimization for Training Deep Models
  • Lesson Module 6: Convolutional Netwroks
  • Lesson Module 7: Sequence Modeling - Recurrent & Recursive Nets
  • Lesson Module 8: Practical Methodology
  • Lesson Module 9: Applications
  • Lesson Module 10: Autoencoders
  • Lesson Module 11: Representation Learning
  • Lesson Module 12: Structured Probabilistic Models for Deep Learning
  • Lesson Module 13: Monte Carlo Methods
  • Lesson Module 14: Confronting the Partition Function
  • Lesson Module 15: Deep Generative Models