Blue Yonder Data Science Consultant Interview Questions and Answers

Q1. About projects and then questions related to ML and DL. Mostly focused on DL part
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Q2. What is the difference between Adam optimizer and Gradient Descent Optimizer?
Ans. 
Adam optimizer is an extension to the Gradient Descent optimizer with adaptive learning rates and momentum.
• Adam optimizer combines the benefits of both AdaGrad and RMSProp optimizers.

• Adam optimizer uses adaptive learning rates for each parameter.

• Gradient Descent optimizer has a fixed learning rate for all parameters.

• Adam optimizer includes momentum to speed up convergence.

• Gradient Descent optimizer updates parameters b...read more
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Q3. When to use Relu and when not?
Ans. 
Use ReLU for hidden layers in deep neural networks, avoid for output layers.
• ReLU is commonly used in hidden layers to introduce non-linearity and speed up convergence.

• Avoid using ReLU in output layers for regression tasks as it can lead to vanishing gradients.

• Consider using Leaky ReLU or Sigmoid for output layers depending on the task.

• ReLU is computationally efficient and helps in preventing the vanishing gradient prob...read more
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Q1. Tell me about yourself
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Q2. Tell me in details about your project. (Mainly the python related project)
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Q3. Which ML algorithm did you use in your project?
Ans. 
I used the Random Forest algorithm in my project.
• Random Forest is an ensemble learning method that combines multiple decision trees to make predictions.

• It is used for both classification and regression tasks.

• Random Forest reduces overfitting and provides feature importance.

• Example: I used Random Forest to predict customer churn in a telecom company.
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Q4. What is Sql? And what is a database?
Ans. 
SQL is a programming language used for managing and manipulating relational databases. A database is a structured collection of data.
• SQL is used to retrieve, insert, update, and delete data from a database.

• A database is a software system that stores and organizes data in a structured manner.

• SQL allows users to define the structure of a database, create tables, and establish relationships between tables.

• Examples of data
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Q5. What do you understand by joins in sql?
Ans. 
Joins in SQL are used to combine rows from two or more tables based on a related column between them.
• Joins are used to retrieve data from multiple tables in a single query.

• Common types of joins include inner join, left join, right join, and full outer join.

• Joins are performed using the JOIN keyword and specifying the columns to join on.

• Joins can be used to combine tables based on matching values or non-matching values.

• ...read more
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Q6. Apply join in the above tables (Table was provided by the interviewer)
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Q7. How many squares are their in a chess box? (Aptitude question)
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I was told about the screening round and the interviewer came with bunch of coding questions which In my opinion I did good. But got rejected.

Standard question from sql and python in hackerrank

Q1. Reverse a linked list
Ans. 
Reverse a linked list by changing the direction of pointers
• Start with three pointers: current, previous, and next

• Iterate through the linked list, updating pointers to reverse the direction

• Return the new head of the reversed linked list
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Q2. Question based on joins and subquery
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Q1. More question about project
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Q2. What do you know about genAI
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Q1. Asked about some machine learning concepts like NLP, TensorFlow etc
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Q1. Tell me about your self
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180 mins of online test with camera ON. Major topics include Excel, Aptitude, Python, Statistics and Case Study

Q1. Explain Apriori Method
Ans. 
Apriori method is a popular algorithm for frequent itemset mining in data mining.
• Used for finding frequent itemsets in transactional databases

• Based on the concept of association rule mining

• Involves generating candidate itemsets and pruning based on support threshold

• Example: If {milk, bread} is a frequent itemset, then {milk} and {bread} are also frequent
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Q2. Explain train-test in Scikit learn
Ans. 
Train-test split is a method used to divide a dataset into training and testing sets for model evaluation in Scikit learn.
• Split the dataset into two subsets: training set and testing set

• Training set is used to train the model, while testing set is used to evaluate the model's performance

• Common split ratios are 70-30 or 80-20 for training and testing sets

• Example: X_train, X_test, y_train, y_test = train_test_split(X, y,
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Q1. Explain about projects in current company
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Q2. Why do you want to move to an individual contributor role from a managerial position
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Q1. Why do you want to join Wolters Kluwer?
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Q2. Discussion around analytics and managerment reporting deliverables in current org.
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