Applied Materials Data Scientist Interview Questions and Answers

Q1. What is Adaboost?
Ans. 
Adaboost is a machine learning algorithm that combines multiple weak learners to create a strong learner.
• Adaboost stands for Adaptive Boosting.

• It works by adjusting the weights of incorrectly classified instances so that subsequent weak learners focus more on them.

• The final prediction is made by combining the predictions of all the weak learners, weighted by their accuracy.

• Example: Adaboost is commonly used in face det...read more
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Q2. Print the binary tree in different order
Ans. 
Printing a binary tree in different orders
• Use inorder traversal to print the binary tree in ascending order

• Use preorder traversal to print the binary tree in root-left-right order

• Use postorder traversal to print the binary tree in left-right-root order
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Binary tree question was asked

Q1. Several tech question related to past projects and random forest etc were asked.
Ans. 
Discussed past projects involving Random Forest and related tech questions in a data science interview.
• Random Forest is an ensemble learning method that combines multiple decision trees to improve accuracy.

• In a past project, I used Random Forest to predict customer churn, achieving an accuracy of 85%.

• Feature importance in Random Forest helps identify which variables contribute most to predictions.

• Hyperparameter tuning,...read more
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Q1. Tell me about yourself and several other questions
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Few standard dsa questions were asked.

Q1. Explain projects
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Q2. Introduce urself
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Based on NLP

Q1. One-on-one with the company CEO.
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Related to NLP

Q1. One-on-one with company CEO
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Q1. Difference between LSTM and BiLSTM
Ans. 
LSTM is a type of recurrent neural network that can remember previous inputs. BiLSTM is a variant that processes input in both directions.
• LSTM stands for Long Short-Term Memory

• LSTM can remember long-term dependencies in data

• BiLSTM processes input in both forward and backward directions

• BiLSTM is useful for tasks such as named entity recognition and sentiment analysis
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