Lesson 1244 of 1524
Deep Learning and AI Basics
The goal of neural networks is for a computer algorithm to be able to classify these digits as well as a human
Practice this chapterThe goal of neural networks is for a computer algorithm to be able to classify these digits as well as a human
deep learning — training and implementation of neural networks with many layers to learn hierarchical (structured) representations of data. bias — value b that is added to the weighted signal, making the neuron more likely (or less likely, if b is negative) to activate on any given input. weight — value w that is multiplied to the incoming signal, essentially determining the strength of the connection. neural network — structure made up of neurons that takes in input and produces output that classifies the input information.
Worked example
What does “deep learning” mean in Deep Learning and AI Basics?
- 1Use the wording this chapter gives for deep learning.
- 2The book says: training and implementation of neural networks with many layers to learn hierarchical (structured) representations of data.
- 3Do not use the meaning of bias. That term means value b that is added to the weighted signal, making the neuron more likely (or less likely, if b is negative) to activate on any given input.
Result: training and implementation of neural networks with many layers to learn hierarchical (structured) representations of data
Why. That is the meaning this chapter gives for deep learning.
Do not swap deep learning and bias. deep learning means training and implementation of neural networks with many layers to learn hierarchical (structured) representations of data. bias means value b that is added to the weighted signal, making the neuron more likely (or less likely, if b is negative) to activate on any given input.
Practice margin
This chapter
A fresh set from this chapter only. Choose 10 or 20. Multiple choice and fill-in, with no repeat inside the set.