Ask Ghassem - Recent questions in Data Science Interview Questions

Do you usually collect you own data or there is always a resource available for you? Or it depends on the company?

Sun, 09 Jan 2022 22:13:34 +0000

Data manipulation problem study resources

Wed, 28 Aug 2019 12:53:53 +0000

A colleague of mine is studying for tech roles, and they're asked to solve a consistent type of problem during the phone screenings: practicing manipulating data (sets, hash tables/dictionaries, arrays/lists, strings). These questions aren’t necessarily difficult problems and tend to require very little logic, and tend to be more about having a good understanding of the data types (such as listed above). I've provided some examples in this link: https://imgur.com/a/ITVeVnr

So I'm wondering if there are resources to study these questions. They aren't really Leetcode questions or the kind of thing found on Reddit daily programmer, which is where I'm generally directed to most often in the time I've been asking all over. Even if it's a textbook, it would be incredibly handy. And to be clear, I'm not looking for like a hack or golden secret, just resources for studying. Thank you for any help!

Do you have a cheatsheet for Data Science?!

Wed, 27 Feb 2019 05:51:00 +0000

What is summary statistics?

Thu, 01 Nov 2018 19:45:16 +0000

What is the difference between univariate and multivariate analysis?

Tue, 30 Oct 2018 11:39:08 +0000

What is the purpose of randomization in statistics?

Tue, 30 Oct 2018 11:35:52 +0000

How will you create a classification to identify key customer trends in unstructured data?

Sun, 28 Oct 2018 11:45:43 +0000

Mention some common problems that data analysts encounter during analysis.

Sun, 28 Oct 2018 11:44:59 +0000

Explain the typical data analysis process.

Sun, 28 Oct 2018 11:43:46 +0000

What is the difference between Data Mining and Data Analysis?

Sun, 28 Oct 2018 11:42:45 +0000

Which scenarios among the following are a valid reason to use regularization?

Sat, 27 Oct 2018 17:31:43 +0000

A. To drop the least useful variables of a model

B. To reduce over-fitting

C. To reduce the bias of a model

D. To decrease p-value

How to transform categorical variable into a matrix binary feature?

Sat, 27 Oct 2018 17:23:08 +0000

Which of the following feature transformations would be a good choice to transform a categorical variable into a matrix binary feature?

A. One-hot-encoding

B. Principal Component Analysis (PCA)

C. Box-Cox

D. Informative prior

What are the main steps in making a decision tree?

Fri, 12 Oct 2018 02:17:19 +0000

Please explain Linear Regression with an example?

Fri, 12 Oct 2018 02:14:00 +0000

How to return the outliers by having a list of numbers ?

Mon, 08 Oct 2018 12:19:22 +0000

What are Natural Language Processing (NLP) and its applications?

Mon, 08 Oct 2018 11:59:52 +0000

What is TF-IDF algorithm?

Mon, 08 Oct 2018 11:57:39 +0000

Can you explain the percentiles and quartiles and their applications?

Mon, 08 Oct 2018 11:52:30 +0000

When should we use Mean, Median or Mode as Measures of Central Tendency?

Wed, 03 Oct 2018 06:06:09 +0000