109 Interview Questions

Explain the difference between L1 and L2 regularization methods.

"A regression model that uses L1 regularization technique is called Lasso Regression and model which uses L2 is called Ridge Regression. The key difference between these two is the penalty term."

What are the different data objects in R?

"R objects can store values as different core data types (referred to as modes in R jargon); these include numeric (both integer and double), character and logical."

What is the difference between SQL and MySQL or SQL Server?

"SQL stands for Structured Query Language. It's a standard language for accessing and manipulating databases. MySQL is a database management system, like SQL Server, Oracle, Informix, Postgres, etc."

What is the difference between a tuple and a list in Python?

"Apart from tuples being immutable there is also a semantic distinction that should guide their usage."

What is the difference between type I vs type II error?

"A type I error occurs when the null hypothesis is true, but is rejected. A type II error occurs when the null hypothesis is false, but erroneously fails to be rejected."

What is root cause analysis?

"All of us dread that meeting where the boss asks 'why is revenue down?' The only thing worse than that question is not having any answers! There are many changes happening in your business every day, and often you will want to understand exactly what is driving a given change — especially if it is unexpected. Understanding the underlying causes of change is known as root cause analysis."

What is a statistical interaction?

"Basically, an interaction is when the effect of one factor (input variable) on the dependent variable (output variable) differs among levels of another factor."

What is sampling? How many sampling methods do you know?

"Data sampling is a statistical analysis technique used to select, manipulate and analyze a representative subset of data points to identify patterns and trends in the larger data set being examined."

What is the best way to use Hadoop and R together for analysis?

"Hadoop and R complement each other quite well in terms of visualization and analytics of big data. There are four different ways of using Hadoop and R together."

What are hash table collisions?

"If the range of key values is larger than the size of our hash table, which is usually always the case, then we must account for the possibility that two different records with two different keys can hash to the same table index. There are a few different ways to resolve this issue. In hash table vernacular, this solution implemented is referred to as collision resolution."

Tell me the difference between an inner join, left join/right join, and union.

"In a Venn diagram the inner join is when both tables have a match, a left join is when there is a match in the left table and the right table is null, a right join is the opposite of a left join, and a full join is all of the data combined."

What is an exact test?

"In statistics, an exact (significance) test is a test where all assumptions, upon which the derivation of the distribution of the test statistic is based, are met as opposed to an approximate test (in which the approximation may be made as close as desired by making the sample size big enough). This will result in a significance test that will have a false rejection rate always equal to the significance level of the test. For example an exact test at significance level 5% will in the long run reject true null hypotheses exactly 5% of the time."

Explain how MapReduce works as simply as possible.

"MapReduce is a programming model that enables distributed processing of large data sets on compute clusters of commodity hardware. Hadoop MapReduce first performs mapping which involves splitting a large file into pieces to make another set of data."

Explain the 80/20 rule, and tell me about its importance in model validation.

"People usually tend to start with a 80-20% split (80% training set - 20% test set) and split the training set once more into a 80-20% ratio to create the validation set."

What are the supported data types in Python?

"Python's built-in (or standard) data types can be grouped into several classes. Sticking to the hierarchy scheme used in the official Python documentation these are numeric types, sequences, sets and mappings."

What is selection bias?

"Selection (or 'sampling') bias occurs in an 'active,' sense when the sample data that is gathered and prepared for modeling has characteristics that are not representative of the true, future population of cases the model will see. That is, active selection bias occurs when a subset of the data are systematically (i.e., non-randomly) excluded from analysis."

What is an example of a data set with a non-Gaussian distribution?

"The Gaussian distribution is part of the Exponential family of distributions, but there are a lot more of them, with the same sort of ease of use, in many cases, and if the person doing the machine learning has a solid grounding in statistics, they can be utilized where appropriate."

What is the Binomial Probability Formula?

"The binomial distribution consists of the probabilities of each of the possible numbers of successes on N trials for independent events that each have a probability of π (the Greek letter pi) of occurring."

What does UNION do? What is the difference between UNION and UNION ALL?

"UNION removes duplicate records (where all columns in the results are the same), UNION ALL does not."

How do you access the element in the 2nd column and 4th row of a matrix named M?

"We can access elements of a matrix using the square bracket [ indexing method. Elements can be accessed as var[row, column]."

What is linear regression? What do the terms p-value, coefficient, and r-squared value mean? What is the significance of each of these components?

A linear regression is a good tool for quick predictive analysis: for example, the price of a house depends on a myriad of factors, such as its size or its location. In order to see the relationship between these variables, we need to build a linear regression, which predicts the line of best fit between them and can help conclude whether or not these two factors have a positive or negative relationship.

What is the purpose of the group functions in SQL? Give some examples of group functions.

Group functions are necessary to get summary statistics of a data set. COUNT, MAX, MIN, AVG, SUM, and DISTINCT are all group functions.

What is the latest data science book / article you read? What is the latest data mining conference / webinar / class / workshop / training you attended?

If you haven't read a good data science book recently, Springboard compiled a list of the best data science books to read! And check out these data science podcasts.

In Python, how is memory managed?

In Python, memory is managed in a private heap space. This means that all the objects and data structures will be located in a private heap. However, the programmer won't be allowed to access this heap. Instead, the Python interpreter will handle it. At the same time, the core API will enable access to some Python tools for the programmer to start coding. The memory manager will allocate the heap space for the Python objects while the inbuilt garbage collector will recycle all the memory that's not being used to boost available heap space.

Is it better to have too many false positives or too many false negatives?

It depends on several factors. Read about this here.

Explain what precision and recall are. How do they relate to the ROC curve?

Recall describes what percentage of true positives are described as positive by the model. Precision describes what percent of positive predictions were correct. The ROC curve shows the relationship between model recall and specificity-specificity being a measure of the percent of true negatives being described as negative by the model. Recall, precision, and the ROC are measures used to identify how useful a given classification model is.

What is the Central Limit Theorem and why is it important?

Suppose that we are interested in estimating the average height among all people. Collecting data for every person in the world is impossible. While we can't obtain a height measurement from everyone in the population, we can still sample some people. The question now becomes, what can we say about the average height of the entire population given a single sample. The Central Limit Theorem addresses this question exactly.

What are two main components of the Hadoop framework?

The Hadoop Distributed File System (HDFS), MapReduce, and YARN.

What are the assumptions required for linear regression?

There are four major assumptions: 1. There is a linear relationship between the dependent variables and the regressors, meaning the model you are creating actually fits the data, 2. The errors or residuals of the data are normally distributed and independent from each other, 3. There is minimal multicollinearity between explanatory variables, and 4. Homoscedasticity. This means the variance around the regression line is the same for all values of the predictor variable.

What are the different types of sorting algorithms available in R language?

There are insertion, bubble, and selection sorting algorithms.

Which data scientists do you admire most? Which startups?

There are plenty of amazing data scientists to choose from—take a look at this article on top data science influencers for interesting information about some of the top data scientists in the world.

If a table contains duplicate rows, does a query result display the duplicate values by default? How can you eliminate duplicate rows from a query result?

Yes. One way you can eliminate duplicate rows with the DISTINCT clause.

How is k-NN different from k-means clustering?

k-NN, or k-nearest neighbors is a classification algorithm, where the k is an integer describing the number of neighboring data points that influence the classification of a given observation. K-means is a clustering algorithm, where the k is an integer describing the number of clusters to be created from the given data.

What is the command used to store R objects in a file?

save (x, file="x.Rdata")