Course details

Fundamentals of Sequence Model: Artificial Neural Network & Sequence Modeling

Fundamentals of Sequence Model: Artificial Neural Network & Sequence Modeling


Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description

Explore artificial neural networks, their essential components, tools, and frameworks for their implementation. Discover the recurrent neural network and how it's implemented.



Expected Duration (hours)
0.6

Lesson Objectives

Fundamentals of Sequence Model: Artificial Neural Network & Sequence Modeling

  • describe artificial neural networks (ANNs) and their features and characteristics
  • list artificial neural network components used to build a model
  • list prominent tools and frameworks used implement sequence models and artificial neural networks
  • describe sequence modeling as it pertains to language models
  • describe recurrent neural networks and their capabilities and components
  • specify RNN types and their implementation features
  • build a recurrent neural network using PyTorch and Google Colab
  • recall ANN characteristics, modeling tools, and architectures and applications of sequence models
  • Course Number:
    it_mlfnsmdj_01_enus

    Expertise Level
    Intermediate