question
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2.02k
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2 values
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0
1
how have you used statistics in your work as a Data Analytics?
Data Analytics
IBM
null
no
no
0
how to encode a categorical variable with thousands of distinct values?
Machine Learning
IBM
null
no
no
0
how would you approach rotating a matrix by 90 degrees clockwise?
Data Analytics
IBM
null
no
no
0
how would you attempt to solve a data science problem?
Data Science
IBM
null
no
no
0
how would you check if a string b is a rotated version of string a?
Machine Learning
IBM
null
no
no
0
how would you describe yourself as a Data Analytics?
Data Analytics
IBM
null
no
no
1
how would you determine whether string b is a rotated version of string a of different lengths?
Machine Learning
IBM
null
no
no
0
how would you estimate the best month to offer a discount on shoes?
Data Analytics
IBM
null
no
no
0
how would you estimate the weekly profit of your favorite restaurant?
Data Analytics
IBM
null
no
no
0
how would you give each rejected applicant a reason why they got rejected for a loan using a binary classification model?
Machine Learning
IBM
null
no
no
0
how would you go about measuring the performance of company?
Data Analytics
IBM
null
no
no
0
how would you handle encoding for a categorical variable with thousands of distinct values?
Data Analytics
IBM
null
no
no
0
how would you implement a rotation of a matrix by 90 degrees clockwise in code?
Data Analytics
IBM
null
no
no
0
how would you leverage transfer learning to build a custom machine learning model?
Machine Learning
IBM
null
no
no
0
how would you structure a database for a ride-sharing platform like uber?
Data Analytics
IBM
null
no
no
0
how you can define data cleaning as a critical part of process?
Data Science
IBM
null
no
no
0
if i want to counterbalance the cons of pursuing a data science or ai journey, where can i find a certification program?
Data Science
IBM
null
no
no
0
implement the k-means clustering algorithm in python from scratch, and return a list of the cluster of each point in the original list in the same order.
Machine Learning
IBM
null
no
no
0
lets say you have a categorical variable with thousands of distinct values, how would you encode it?
Data Science
IBM
null
no
no
0
list down the conditions for overfitting and underfitting
Data Science
IBM
null
no
no
0
mention some of the main challenges in Machine Learning.
Machine Learning
IBM
null
no
no
0
once you have the data, how would you use it to calculate an estimate?
Data Analytics
IBM
null
no
no
0
retrieve the total cost of all transactions by user, arranging the results in descending order based on the total cost.
Data Analytics
IBM
null
no
no
0
suppose there is a dataset having variables with missing values of more than 30%, how will you deal with such a dataset?
Data Science
IBM
null
no
no
0
suppose we have a binary classification model that classifies whether or not an applicant should be qualified to get a loan. given we dont have access to the feature weights, how would we give each rejected applicant a reason why they got rejected?
Machine Learning
IBM
null
no
no
0
suppose you are asked to run a two-week-long a/b test to test an increase in pricing. how would you approach designing this test?
Data Analytics
IBM
null
no
no
0
tell me about a data problem that challenged you.
Data Analytics
IBM
null
no
no
0
tell me about a time when you exceeded expectations during a project. what did you do, and how did you accomplish it?
All
IBM
null
no
yes
1
tell me about a time when you experienced a difficult problem in your data science career. how did you approach and resolve it?
All
IBM
null
no
yes
0
tell me about a time when you got unexpected results.
Data Analytics
IBM
null
no
yes
0
tell me about yourself.
Data Analytics
IBM
null
no
no
1
what approach would you present for the svm question?
Machine Learning
IBM
null
no
no
0
what are decision trees?
Machine Learning
IBM
null
no
no
0
what are eigenvectors and eigenvalues?
Data Science
IBM
null
no
no
0
what are feature vectors in the context of machine learning?
Machine Learning
IBM
null
no
no
0
what are index and match functions, and how do they work together?
Data Analytics
IBM
null
no
no
0
what are recommender systems?
Data Science
IBM
null
no
no
0
what are some common ai use cases in business?
Machine Learning
IBM
null
no
no
0
what are some commonly used artificial neural networks?
Machine Learning
IBM
null
no
no
0
what are some differences between classification and regression?
Machine Learning
IBM
null
no
no
0
what are some key ct terms?
Data Analytics
IBM
null
no
no
0
what are some of the techniques used for sampling?
Data Science
IBM
null
no
no
0
what are the architecture and components of a convolutional neural network (cnn)?
Machine Learning
IBM
null
no
no
0
what are the available feature selection methods for selecting the right variables for building efficient predictive models?
Data Science
IBM
null
no
no
0
what are the clarifying questions to ask for the svm question?
Machine Learning
IBM
null
no
no
0
what are the differences between correlation and covariance?
Data Science
IBM
null
no
no
0
what are the trade-off between bias and variance in machine learning models?
Machine Learning
IBM
null
no
no
0
what are the types of Machine Learning?
Machine Learning
IBM
null
no
no
0
what are various steps involved in an analytics project?
Data Science
IBM
null
no
no
0
what are z- and t-tests, and when should one be used over the other?
Data Science
IBM
null
no
no
0
what challenges did you face?
Data Science
IBM
null
no
no
0
what data analytics software are you familiar with?
Data Analytics
IBM
null
no
no
0
what data analytics software are you trained in?
Data Analytics
IBM
null
no
no
0
what data software have you used in the past?
Data Analytics
IBM
null
no
no
0
what do Data Analyticss do?
Data Analytics
IBM
null
no
no
0
what do you mean by word data science?
Data Science
IBM
null
no
no
0
what do you understand about imbalanced data?
Data Science
IBM
null
no
no
0
what do you understand about stochastic gradient descent?
Data Science
IBM
null
no
no
0
what do you understand by letter r?
Data Science
IBM
null
no
no
0
what do you understand by survivorship bias?
Data Science
IBM
null
no
no
0
what do you understand by term hash table collisions?
Data Science
IBM
null
no
no
0
what does it mean when the p-values are high and low?
Data Science
IBM
null
no
no
0
are there any key success indicators for someone serving a role like Data Science?
Data Analytics
Intel
null
no
no
1
between python and r, which one will you choose for analyzing the text, and why?
Data Science
Intel
null
no
no
0
build a logistic regression model on the customer_churn dataset in python. the dependent variable is churn and the independent variable is monthlycharges. find the log_loss of the model.
Data Science
Intel
null
no
no
0
calculate the rmse values for the model building.
Data Science
Intel
null
no
no
0
can you avoid overfitting your model?
Data Science
Intel
null
no
no
0
can you describe your experience with incident response?
Data Analytics
Intel
null
no
yes
0
can you explain a complex technical concept related to threat intelligence in non-technical terms?
Data Analytics
Intel
null
no
no
1
can you share an example of how you have applied threat intelligence to prevent an attack?
Data Analytics
Intel
null
no
no
1
can you tell me about a time when you made a decision that didn't work out?
Data Analytics
Intel
null
no
yes
1
can you tell me about a time when you made a decision that didn't work out? what did you learn as a result of this?
Data Analytics
Intel
null
no
yes
1
can you tell me about a time you discovered a threat that wasn't previously known?
Data Analytics
Intel
null
no
no
0
can you tell us about a time where you received unpleasant feedback?
Data Analytics
Intel
null
no
no
1
can you walk me through the threat intelligence analysis process?
Data Analytics
Intel
null
no
no
0
could you explain how cross-validation is used to assess the performance of a machine learning model?
Machine Learning
Intel
null
no
no
0
could you outline the process of setting up an a/b test for this purpose?
Data Analytics
Intel
null
no
no
0
define neural networks and its types
Data Science
Intel
null
no
no
0
define the terms kpi, lift, model fitting, robustness, and doe.
Data Science
Intel
null
no
no
0
difference between point estimates and confidence interval.
Data Science
Intel
null
no
no
0
differentiate between data analytics and data science
Data Science
Intel
null
no
no
0
explain bagging in data science.
Data Science
Intel
null
no
no
0
explain boosting in data science.
Data Science
Intel
null
no
no
0
explain collaborative filtering in recommender systems.
Data Science
Intel
null
no
no
0
explain content-based filtering in recommender systems.
Data Science
Intel
null
no
no
0
explain how a recommender system works.
Data Science
Intel
null
no
no
0
explain how machine learning is different from Machine Learning.
Data Science
Intel
null
no
no
0
explain information gain and its importance in constructing a decision tree.
Data Science
Intel
null
no
no
0
explain selection bias.
Data Science
Intel
null
no
no
0
explain stacking in data science.
Data Science
Intel
null
no
no
0
explain tf/idf vectorization.
Data Science
Intel
null
no
no
0
explain the differences between supervised and unsupervised learning.
Data Science
Intel
null
no
no
0
explain the purpose of data cleaning
Data Science
Intel
null
no
no
0
explain univariate, bivariate, and multivariate analyses.
Data Science
Intel
null
no
no
0
give an example of collaboration with other teams?
Data Analytics
Intel
null
no
no
1
have you ever had to disagree with a member of your team?
Data Analytics
Intel
null
no
no
1
how are data science and machine learning related to each other?
Data Science
Intel
null
no
no
0
how are the values of the 'target' column converted in the logistic regression implementation in r?
Data Science
Intel
null
no
no
0
how can time-series data be declared as stationery?
Data Science
Intel
null
no
no
0
how can we deal with outliers?
Data Science
Intel
null
no
no
0