Submission information
Submission Number: 197
Submission ID: 4054
Submission UUID: f98e24be-468f-4c78-8a57-c96713868d38
Submission URI: /form/resource
Created: Thu, 09/28/2023 - 15:00
Completed: Thu, 09/28/2023 - 15:02
Changed: Fri, 03/14/2025 - 11:43
Remote IP address: 50.217.59.154
Submitted by: Robin Hwang
Language: English
Is draft: No
Webform: Knowledge Base Resources
Approved: Yes
Title: Feed Forward NNs and Gradient Descent
Category: Website
Skill Level:
Intermediate (305)
Description:
Feed-forward neural networks are a simple type of network that simply rely on
data to be "fed-forward" through a series of layers that makes decisions on
how to categorize datum. Gradient descent is a type of optimization tool that
is often used to train machines. These two areas in ML are good starting
points and are the easiest types of neural network/optimization to
understand.
Link to Resource:
- Feed-Forward and SGD (https://medium.com/jun94-devpblog/dl-2-feed-forward-network-dc9c01b9d832)
Tags:
deep-learning (303), machine-learning (272), neural-networks (435)
Domain:
ACCESS CSSN (780), Campus Champions (572), CAREERS (323), CCMNet (835), Great Plains (311), Kentucky (322), Northeast (308)
Would you like to associate this resource with an Affinity Group?: {Empty}