Peeush Agarwal peeush-agarwal

peeush-agarwal / handle_multicollinearity_by_VIF.py

Created May 12, 2024 07:48

Handle multicollinearity using VIF and dropping correlated columns with higher VIF value

	def multicollinearity_by_vif(X, vif=5):
	"""Remove columns from X whose VIF is greater than supplied 'vif'
	Parameters:
	X:array or dataframe containing data excluding target variable
	vif: int or float of limiting value of VIF
	Note:
	This function changes X inplace
	"""
	import statsmodels.api as sm
	from statsmodels.stats.outliers_influence import variance_inflation_factor

peeush-agarwal / handle_outliers_eliminate_rows.py

Last active May 12, 2024 07:35

Handle outliers using IQR and eliminate rows

	import numpy as np

	# data as pandas DataFrame
	train = ...

	# Variables to store out bounds by column value
	upper_bounds = {}
	lower_bounds = {}

	# Best practice

peeush-agarwal / resume.json

Last active September 18, 2024 10:48

	{
	"basics": {
	"name": "Peeush Agarwal",
	"label": "Senior ML Engineer",
	"email": "agarwal.peeush@gmail.com",
	"phone": "+91 82377 28795",
	"location": {
	"city": "Pune",
	"region": "Maharashtra",
	"countryCode": "IN"

peeush-agarwal / resume_mg.json

Last active September 18, 2024 10:22

Resume in JSON format for Megha

	{
	"basics": {
	"name": "Megha Goyal",
	"label": "WFM Business Partner \| Chief of Staff \| MIS Executive",
	"email": "meghagoyal0602@gmail.com",
	"phone": "+91-90961 69255",
	"location": {
	"address": "Wagholi",
	"city": "Pune",
	"region": "Maharashtra"

peeush-agarwal / compute_eigen_vals.py

Created March 14, 2022 17:25

PCA: computation of eigen values for the dataframe

	import numpy as np

	cov_mat = np.cov(X_train_std.T)
	eigen_vals, eigen_vecs = np.linalg.eig(cov_mat)

peeush-agarwal / standardize_data.py

Created March 14, 2022 17:23

PCA: standardize the wine dataframe

	from sklearn.model_selection import train_test_split
	from sklearn.preprocessing import StandardScaler

	# split into training and testing sets
	X, y = df_wine.iloc[:, 1:].values, df_wine.iloc[:, 0].values
	X_train, X_test, y_train, y_test = train_test_split(
	X, y, test_size=0.3,
	stratify=y, random_state=0
	)
	# standardize the features

peeush-agarwal / load_wine_data.py

Created March 14, 2022 17:19

PCA: load wine data into the dataframe

	import pandas as pd

	df_wine = pd.read_csv('https://archive.ics.uci.edu/ml/'
	'machine-learning-databases/wine/wine.data',
	header=None)
	df_wine.head()

peeush-agarwal / main.yml

Last active February 28, 2022 02:58

GitHub workflow file changes with docker container

	# This is a basic workflow to help you get started with Actions

	name: Deploy to Raspberry Pi

	# Controls when the workflow will run
	on:
	# Triggers the workflow on push or pull request events but only for the main branch
	push:
	branches: [ main ]

peeush-agarwal / .dockerignore

Created February 27, 2022 16:13

Docker ignore file to ignore specific files and folders when building Docker container

	Dockerfile
	__pycache__/

peeush-agarwal / gunicorn_starter.sh

Created February 27, 2022 04:26

Gunicorn server shell script

	#!/bin/sh
	gunicorn -w 1 -b 0.0.0.0:4000 app:app