Skip to content

Implemented Logistic Regression, Multi-class Logistic Regression and, Artificial Neural Networks from scratch using Python

Notifications You must be signed in to change notification settings

chandukasturi/Logistic_Regression

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Logistic_Regression

Implemented Logistic Regression, Multi-class Logistic Regression and, Artificial Neural Networks from scratch using Python

File naming convention and Description

q1.ipynb : This file contains the python implementation of the first problem-Logistic Regression.

q2.ipynb : This file contains the python implementation of the second problem-multiclass Logistic Regression.

q3.ipynb : This file contains the python implementation of the third problem-ANN

Report.pdf: This file consists of the entire summarization of the results acquired by the above python codes.

Execution of the above files

  1. You will need to install any latest version Python-3

  2. You will need Anaconda to execute the above submitted python code.Anconda is required as it installs all the necessary packages for importing such as numpy,random...etc

  3. After installing anaconda use -pip install notebook command to install jupyter notebook

  4. Open jupyter notebook kernel by typing a command in the anaconda prompt $jupyter notebook -- command to open jupyter notebook

  5. Open the files in jupyter notebook by selecting the open file option in the jupyter notebook

  6. Run the files in individual kernels or files.

or you can change the directory to the destination folder and enter jupyter notebook command to open the files in jupyter notebook

About

Implemented Logistic Regression, Multi-class Logistic Regression and, Artificial Neural Networks from scratch using Python

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published