Deep Learning Foundation – Syllabus

Module 1 – Introduction to Deep Learning

  • Deep Learning: The Series Introduction
  • What is a Neural Network
  • Three reasons to go Deep
  • Your choice of Deep Net
  • Deep Learning Market

Module 2 – Deep Learning Models

  • Restricted Boltzmann Machines
  • Deep Belief Network
  • Convolutional Network
  • Recurrent Network

Module 3 – Additional Deep Learning Models

  • Autoencoders
  • Recursive Neural Tensor Network
  • Generative Adversarial Networks

Module 4 – Deep Learning Platforms & Libraries

  • What is a Deep Net Platform
  • H2O ai
  • Dato GraphLab
  • What is a Deep Learning Library
  • Theano
  • Caffe
  • TensorFlow
  • Keras

Who this course is for:

  • Deep Learning Scientists
  • Machine Learning Engineers
  • Data Scientists & Senior Data Scientists
  • Newbies and Beginners aspiring for a career in Deep Learning and Machine Learning
  • AI Researchers – Complex Algorithms, Deep Learning Models
  • Deep Learning Researchers / Development Engineers
  • Data Consultants & Analysts
  • Computer Vision Engineers
  • Data Science & Artificial Intelligence Managers
  • Individuals interested in learning the fundamentals of Deep Learning
  • Deep Learning Interns
  • Software Engineers and Advanced Programmers
  • Optimization Analysts
  • Technology Consultants
  • Big Data Scientists

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