Ira Joshi

Google Maps API v3: How to remove all markers?

To map clear markers, you can try using the following: 1. Declare a global variable like this: var markersArray = []; 2. Define a function like this: function clearOverlays() { for (var i = 0; i < markersArray xss=removed xss=removed xss=removed xss=removed>3. Push markers in the 'markerArray' before calling the…

Devops

Answered Jul 12, 2021 · 2.3K Views Read answer →

SSRS expression switch/Else if

To resolve ssrs switch: Syntax for case statement in SSRS:Switch(Expression as Object) Syntax for IIF() statement in SSRS: =IIF( Expression to evaluate, what-to-do when the expression is true, what-to-do when the expression is false ) Try to implement this variation of your first expression:…

Python

Answered May 17, 2021 · 1.2K Views Read answer →

Failed to start mongod.service: Unit mongod.service not found

In case, you failed to start mongod.service: unit mongod.service not found then you should use unit mongodb.service is masked. Use the following command to unmask it. sudo systemctl unmask mongodband after that re-run the below-mentioned command:- sudo service mongod start

Spark

Answered May 11, 2021 · 2.6K Views Read answer →

Python Pandas: Find the length of the string in dataframe

To find the length of strings in a data frame you have the len method on the dataframes str property. But to do this you need to call this method on the column that contains the string data. You can find the length of dataframe using the below code: import pandas as pd data = pd.DataFrame({ 'age' : [15, 17, 20, 14,…

Python

Answered Apr 14, 2021 · 12.1K Views Read answer →

RSA encryption and decryption in Python

Python

Answered Mar 7, 2021 · 1.5K Views Read answer →

Explain Tf-Idf and explain how to compute the same?

Tf-idf or term frequency-inverse document frequency, is a measure of weight often used in information retrieval and text mining techniques. This weight is a statistical measure which is used to evaluate the importance of a word to a document in a collection or corpus. The weight increases proportionally to the number…

Data Science

Answered Dec 24, 2019 · 1.8K Views Read answer →

A user is trying to create a knn classification model using the knn method from R class package:

impens_test_pred

Data Science

Answered Dec 20, 2019 · 1.6K Views Read answer →

A project contains a fake advertising data set, indicating whether or not a particular internet user clicked on an Advertisement on a company website. Try to create a model that will predict whether…

We will import the librariesNow we import the dataset and check the columns

Data Science

Answered Nov 30, 2019 · 1.8K Views Read answer →

Explain Akaike Information criteria.

Akaike Information Criteria or AIC, in simple words, is a trade-off between bias versus variance. It helps to calculate the relative quality of a statistical model for a given data. Mostly when AIC is compared between two models, the model with the least AIC is preferred. AIC = -2*ln(L) + 2*k L = Maximum value of…

Data Science

Answered Nov 30, 2019 · 1.5K Views Read answer →

Explain how to implement decision tree in python

Initially we import the libraries and the dataset import numpy as np import pandas as pd import matplotlib.pyplot as plt data = pd.read_csv("Fraud_check.csv") data.head() Now we discretize the data data.TaxableIncome.max() data['TaxableIncome'] = pd.cut(data['TaxableIncome&

Data Science

Answered Nov 17, 2019 · 1.5K Views Read answer →

Mention some examples where precision and recall can be a dangerous call.

Precision and recall are two of the evaluation techniques used in a machine learning model which tells us how better a model can perform. But there are certain business domains where these two evaluation techniques can cause a business risk.

Data Science

Answered Nov 16, 2019 · 1.5K Views Read answer →

Visualize a decision tree regression using Python

Let us import the model # Importing the libraries import numpy as np import matplotlib.pyplot as plt import pandas as pd # Importing the dataset dataset = pd.read_csv('Position_Salaries.csv') X = dataset.iloc[:, 1:2].values y = dataset.iloc[:, 2].values

Data Science

Answered Nov 9, 2019 · 1.8K Views Read answer →