Course details

Build & Train RNNs: Neural Network Components

Build & Train RNNs: Neural Network Components


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore artificial neural network and the components of neural networks and examine the concept of learning and training samples used in Supervised, Unsupervised and Reinforcement learning.



Expected Duration (hours)
0.6

Lesson Objectives

Build & Train RNNs: Neural Network Components

  • describe artificial neural network and its components
  • identify the topology of the networks that implements feedforward, recurrent and linked networks
  • list activation mechanisms used in the implementation of neural networks
  • specify the prominent learning samples that can be applied in neural networks
  • compare Supervised, Unsupervised, and Reinforcement learning samples
  • describe training samples and the approaches for building them
  • identify training sets and recognize patterns
  • recognize the need for gradient optimization in neural networks
  • list neural network components, activation functions, learning samples, and gradient descent optimization algorithms
  • Course Number:
    it_mlbtrndj_01_enus

    Expertise Level
    Intermediate