TCS Work From Home: IT Giant May Allow Some Staff To Continue WFH Forever, Know IT Giant's Mega Plan


Narayan Murthy, founder of Infosys, recently mentioned that he was not a fan of working from home since it "lowers productivity". Murthy is of the view that work from office was needed as there has to be a demarcation between office and work.


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Learning and Practicing SQL: Resources and Platforms

1. https://sqlbolt.com/
2. https://sqlzoo.net/
3. https://www.codecademy.com/learn/learn-sql
4. https://www.w3schools.com/sql/
5. https://www.hackerrank.com/domains/sql
6. https://www.windowfunctions.com/
7. https://selectstarsql.com/
8. https://quip.com/2gwZArKuWk7W
9. https://leetcode.com/problemset/database/
10. http://thedatamonk.com

DATA SCIENCE INTERVIEW QUESTIONS WITH ANSWERS


1. What is a logistic function? What is the range of values of a logistic function?

f(z) = 1/(1+e -z )
The values of a logistic function will range from 0 to 1. The values of Z will vary from -infinity to +infinity.


2. What is the difference between R square and adjusted R square?

R square and adjusted R square values are used for model validation in case of linear regression. R square indicates the variation of all the independent variables on the dependent variable. i.e. it considers all the independent variable to explain the variation. In the case of Adjusted R squared, it considers only significant variables(P values less than 0.05) to indicate the percentage of variation in the model.

Thus Adjusted R2 is always lesser then R2.


3. What is stratify in Train_test_split?

Stratification means that the train_test_split method returns training and test subsets that have the same proportions of class labels as the input dataset. So if my input data has 60% 0's and 40% 1's as my class label, then my train and test dataset will also have the similar proportions.


4. What is Backpropagation in Artificial Neuron Network?

Backpropagation is the method of fine-tuning the weights of a neural network based on the error rate obtained in the previous epoch (i.e., iteration). Proper tuning of the weights allows you to reduce error rates and make the model reliable by increasing its generalization.

ENJOY LEARNING 👍👍

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