/ML_Practice_Workbooks

Practice workbooks for logistic and linear regression

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

ML Practice Workbooks

What is this repository about? There are several python notebooks and codes which are part of this folder. These are just some simple practice problems attempted by me including linear regression, logistic regression, and EDA on some datasets. The codes dont follow best practices (are not commented properly, have hard coded variables everywhere etc.). Apologies, it is messy.

For running the code, you may follow the below steps:

  1. Run VSCode (or any other code editor) from Anaconda Command Prompt

  2. Make sure you are using a dedicated virtual environment and activate it, sample - '''code conda create -n myenv python=3.7.3 '''

  3. Install or upgrade all packages from requirements.txt conda install --file requirements.txt or pip install -r requirements.txt You may need to add the full path of requirements.txt file depending on your pwd

  4. You would have to change all data paths accordingly.

Important links:

  1. Conda environment - https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
  2. https://wiki.epfl.ch/help-git-en/how-can-i-import-an-existing-folder-into-my-repository

Folders & Code Description -

data - This folder contains all data files for the different workbooks & codes

Notebooks

  1. Bank Defaulter Prediction contains Bank_Term.ipynb which implements logistic regression
  2. Hospital Profiling contains two notebooks which does EDA of hospital data (Data unavailable)
  3. Spam Identification contains Email_Spam.ipynb which focuses on EDA of email data
  4. House Prices module contains Predicting_house_prices.ipynb which implents linear regression