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Neural Networks


Overview/Description
Target Audience
Prerequisites
Expected Duration
Lesson Objectives
Course Number
Expertise Level



Overview/Description
Due to recent advancements in processing, neural networks have become easier to train, which made them extremely popular. In this course, you will learn about neural networks and how to use them.

Target Audience
Anyone interested in understanding machine learning and using it to solve problems

Prerequisites
None

Expected Duration (hours)
0.7

Lesson Objectives

Neural Networks

  • start the course
  • describe neural networks and their capabilities
  • describe how different neural networks are structured
  • describe how cost functions are used to train neural networks
  • describe activation functions and list different types of commonly used activation functions
  • describe feedforward neural networks and the intuition behind calculating gradients in neural networks
  • describe how to use backpropagation for more efficient neural network training
  • describe batch learning and why it makes neural network training easier
  • describe TensorFlow and its high-level architecture
  • set up TensorFlow for use on a CPU
  • import data into TensorFlow using built-in data sources and external data sources
  • build and train a single-layer neural network in TensorFlow
  • build and train a multilayer neural network in TensorFlow
  • describe neural networks, network layers, cost functions, activation functions, and gradient descent
  • Course Number:
    sd_exml_a04_it_enus

    Expertise Level
    Intermediate