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Vishal Ranjan vishivish18

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2.0

AI Consultant #Developer #Dreamer #Traveller

vishivish18 / mlop_session_vi-working-copy.ipynb

Created January 7, 2022 10:19

MLOP_Session_VI-Working Copy.ipynb

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vishivish18 / pre-commit-eslint

Created April 29, 2020 17:43 — forked from shettayyy/pre-commit-eslint

Pre-commit hook for Linting JS with ESLint before commit.

	#!/bin/sh

	STAGED_FILES=$(git diff --cached --name-only --diff-filter=ACM \| grep ".jsx\{0,1\}$")
	ESLINT="$(git rev-parse --show-toplevel)/node_modules/.bin/eslint"

	if [[ "$STAGED_FILES" = "" ]]; then
	exit 0
	fi

	PASS=true

vishivish18 / welcome-to-hogwarts.js

Created January 18, 2019 08:40

	var wizard = {
	schoolName: 'Hogwarts',
	headMaster: 'Professor Dumbeldore ',
	getWizardName: function(firstname, lastname) {
	var fullname = firstname + ' ' + lastname;
	return fullname;
	},
	getSchoolNameAndHeadMaster: function(){
	return this.headMaster + " will be your headMaster at "+ this.schoolName
	}

vishivish18 / gsmkdirs.sh

Created September 22, 2018 09:41 — forked from xmedeko/gsmkdirs.sh

Google Cloud Bucket: create explicit dirs

	#!/bin/bash

	##
	## Creates explicit dirs on the bucket
	##

	function print_help() {
	echo "Usage:" $(basename $0) bucket_mounted_dir
	exit 1
	}

vishivish18 / OAuth.js

Created January 18, 2018 09:14

	$scope.registerWithFacebook = function() {
	FB.getLoginStatus(function(response) {
	if (response.status === 'connected') {
	console.log("Here")
	// Logged into your app and Facebook.
	$scope.testAPI();
	} else {
	// The person is not logged into your app or we are unable to tell.
	document.getElementById('status').innerHTML = 'Please log ' +
	'into this app.';

vishivish18 / own-classifier-1.py

Created October 11, 2017 11:14

	from scipy.spatial import distance

	def euc(a,b):
	return distance.euclidean(a,b)

	class BareBonesKNN():
	def fit(self, x_train, y_train):
	self.x_train = x_train
	self.y_train = y_train
	pass

vishivish18 / iris2.py

Created October 11, 2017 11:04

	import numpy as np
	from sklearn.datasets import load_iris
	from sklearn import tree


	iris = load_iris()
	test_idx = [0, 50, 100]

	#training data
	train_target = np.delete(iris.target, test_idx)

vishivish18 / iris.py

Created October 11, 2017 10:54

	from sklearn.datasets import load_iris
	iris = load_iris()
	print (iris.feature_names)
	print (iris.target_names)
	print (iris.data[0])
	print (iris.target[0])

	for i in range(len(iris.target)):
	print ("Example %d: label %s, features %s" % (i, iris.target[i],iris.data[i]))

vishivish18 / hello_world-1.py

Created October 11, 2017 08:58

	from sklearn import tree
	features = [[140, "smooth"], [130, "smooth"], [150, "bumpy"], [170, "bumpy"]]
	labels = ["apple", "apple", "orange", "orange"]


	clf = tree.DecisionTreeClassifier()
	clf = clf.fit(features, labels)

vishivish18 / hello_world.py

Created October 10, 2017 10:14

	from sklearn import tree
	#import sklearn
	# features = [[140, "smooth"], [130, "smooth"], [150, "bumpy"], [170, "bumpy"]]
	# labels = ["apple", "apple", "orange", "orange"]
	features = [[140, "1"], [130, "1"], [150, "0"], [170, "0"]]
	labels = ["0", "0", "1", "1"]

	clf = tree.DecisionTreeClassifier()
	clf = clf.fit(features, labels)