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 (ANNs), their essential components, tools, and frameworks for their implementation in machine learning solutions. In this 9-video course, you will discover recurrent neural networks (RNNs) and how they are implemented. Key concepts covered here include perceptrons and the computational role they play in ANNs; learning features and characteristics of ANNs and how components are used to build a model; and learning prominent tools and frameworks used to implement sequence models and ANNs. Next, you will learn about sequence modeling as it pertains to language models; RNNs and their capabilities and components; and how to specify RNN types and their implementation features. Learners will then explore the concept of linear and nonlinear functions and classify how they are used with perceptrons; explore the concept of backpropagation and usage of backpropagation algorithm in neural networks; and examine the concept of activation functions and how linear and nonlinear activations are utilized in neural networks. Finally, you will see how to implement perceptrons with Python, and how to use modeling tools and architectures and applications of sequence models.



Expected Duration (hours)
0.6

Lesson Objectives

Fundamentals of Sequence Model: Artificial Neural Network & Sequence Modeling

  • Course Overview
  • 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