Skip to content

This is a project to recognize cat using logistic regression with Neural Network concepts of backward and forward propagation from DeepLearning.AI.

Notifications You must be signed in to change notification settings

CS-Ponkoj/Cat-Recognition-Logistic_Regression_with_a_Neural_Network_mindset

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 

Repository files navigation

Logistic_Regression_with_a_Neural_Network_mindset_v6a

Welcome to your first (required) programming assignment! You will build a logistic regression classifier to recognize cats. This assignment will step you through how to do this with a Neural Network mindset, and so will also hone your intuitions about deep learning.

Instructions:

Do not use loops (for/while) in your code, unless the instructions explicitly ask you to do so. You will learn to:

Build the general architecture of a learning algorithm, including: Initializing parameters Calculating the cost function and its gradient Using an optimization algorithm (gradient descent) Gather all three functions above into a main model function, in the right order

About

This is a project to recognize cat using logistic regression with Neural Network concepts of backward and forward propagation from DeepLearning.AI.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published