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