erwin data modeler machine learning interview questions

Erwin data modeler machine learning interview questions how to#

We have split the interview questions into categories for beginners, intermediate, advanced, business analysts, etc. Popular Data Modeling Interview Questions and Answers to Know in 2024

FAQs on Data Modeling Interview Questions.

Data Science Modeling Interview Questions.

Data Warehouse Modeling Interview Questions.

Data Vault Modeling Interview Questions.

Redshift Data Modeling Interview Questions.

Power BI Data Modeling Interview Questions.

Snowflake Data Modeling Interview Questions.

Oracle Data Modeling Interview Questions and Answers.

Salesforce Data Modeling Interview Questions.

SAP Hana Data Modeling Interview Questions.

Accenture Data Modeling Interview Questions.

Facebook Data Modeling Interview Questions.

Data Modeling Interview Questions Amazon.

Scenario-based Data Modeling Interview Questions.

Data Modeling Interview Questions for Business Analysts.

Data Modeling Interview Questions for Experienced.

Advanced Interview Questions on Data Modeling.

Intermediate Data Modeling Interview Questions.Beginners Data Modeling Interview Questions.Popular Data Modeling Interview Questions and Answers to Know in 2024.You are given a function and a data point. What are eigen-values and eigen-vectors ? Why do we care about them ? What is joint probability and what is conditional probability ? What is a valid probability distribution ? What are the difference ways in which you can represent a document ? Basic Math Questions for Data Science What are popular python libraries you will use for NLP ?

Erwin data modeler machine learning interview questions how to#

How to measure the effectiveness of a model for spam filtering? Note that this is a highly imbalanced problem. I want to find topics in a set of documents, what models will I use ? How do you determine if two sentences are similar ?Įxplain how you can approach sentiment analysis from twitter ? What are various ways of finding word embeddings ?Įxplain the skip-gram model and word2vec embeddings? What are stop words ? How do we remove them ? What is an attention mechanism ? What are some examples where it is used ? Basic NLP Questions What is the difference between a GRU and a bi-directional LSTM ? What is the purpose of an LSTM ? Why do you need a bi-directional LSTM ? What are the differences between keras, tensorflow and pytorch ? How do you fix the number of layers & hidden units in a deep neural network ? How do you typically initialize weights in deep neural network ? What are the learning algorithms you are aware of ? What are the different forms of regularizers used in deep learning ? What are the different loss functions you can use in Deep Learning ? How do you pick one ? What is machine learning and where does deep learning fit in ? How do you make a combined file with these in pandas ? Basic Deep Learning Questions You have one file with person ID, eye color, ethnicity, height, weight in one file and person ID, salary, family size in another file. You have a column that contains colors such as “red”, “blue”,… how do you handle this column ? How do you figure out if you need all of them. You realize you have duplicates in your data – what do you do ? What do you do when you have very little training data ? When do you need to normalize your data to have zero mean and unit variance ? What pre-processing can you do when you have an imbalanced dataset ?

How do you detect outliers in data ? How do you deal with them ? How do you overcome them? Basic Data Cleanup/wrangling Questions What is overfitting and underfitting ? Give examples. What data cleanup and normalization is required in a typical Machine Learning pipeline ? What are the various steps in the typical Machine Learning pipeline ? What is regularization ? What types of regularizers do you know ? Why do you need dimensionality reduction ? What are some ways to do this ? What are popular clustering algorithms? How do you fix the number of clusters in a clustering algorithm ? When are deep learning algorithms more appropriate compared to traditional machine learning algorithms? What is the difference between supervised and unsupervised learning ? What is bias variance trade-off in Machine Learning ? Why do you need training set, test set and validation set ? How do you evaluate a Machine Learning algorithm ?

(Note: There are sevaral more questions along with answers in the main menu “Interview Questions and Answers” ) Basic Data Science Questions We have put them in five categories for convenience. Whether you are kickstarting your interview preparation, or wrapping up your preparation and are looking for final touches, here are over 50 must see questions to prepare for a data science interview.