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Phenom Machine Learning Engineer Intern Interview Questions, Process, and Tips
Phenom Machine Learning Engineer Intern Interview Experiences
1 interview found
Selected
I applied via Referral and was interviewed before Jun 2023. There were 2 interview rounds.
(3 Questions)
- Q1. Different gradient optimizations.
- Ans.
Different gradient optimization algorithms improve training efficiency in machine learning models.
Gradient Descent: Basic optimization algorithm that updates parameters in the opposite direction of the gradient.
Stochastic Gradient Descent (SGD): Updates parameters using a subset of training data at each iteration.
Mini-batch Gradient Descent: Combines features of both Gradient Descent and SGD by using a small batch of t...
- Q2. CNNs vs MLP vs RNNs
- Ans.
CNNs are used for image recognition, MLPs for simple classification tasks, and RNNs for sequential data like text or time series.
CNNs are best suited for image recognition tasks due to their ability to capture spatial dependencies.
MLPs are commonly used for simple classification tasks where the input features are independent of each other.
RNNs are ideal for sequential data like text or time series where the order of in...
- Q3. String match DP problem.
- Ans.
String match DP problem involves finding the longest common subsequence between two strings.
Use dynamic programming to solve this problem efficiently.
Create a 2D array to store the lengths of common subsequences.
Iterate through the strings to fill the array and find the longest common subsequence.
Example: Given strings 'ABCD' and 'ACD', the longest common subsequence is 'ACD'.
(2 Questions)
- Q1. Questions related to projects
- Q2. Different ways to tackle data imbalances, missing data, etc.
- Ans.
Various techniques like resampling, data augmentation, imputation, and ensemble methods can be used to tackle data imbalances and missing data.
Resampling techniques like oversampling (SMOTE) and undersampling can balance class distribution.
Data augmentation methods like generating synthetic data points can help in increasing the size of the minority class.
Imputation techniques like mean, median, mode imputation can be ...
Interview Preparation Tips
Skills evaluated in this interview
Interview questions from similar companies
Not so tough and you will learn a lot of things that are new to you
The duration is about 90 minute
Senior Machine Learning Engineer Interview Questions & Answers
Atlassian
Anonymous
posted on 6 Jan 2025
I applied via Referral and was interviewed in Dec 2024. There was 1 interview round.
Basic data structure coding.
(2 Questions)
- Q1. Train a Decision Tree based on dataset provided?
- Ans.
Train a Decision Tree based on provided dataset.
Preprocess the dataset by handling missing values and encoding categorical variables.
Split the dataset into training and testing sets.
Train the Decision Tree model on the training set.
Evaluate the model's performance on the testing set using metrics like accuracy or F1 score.
- Q2. How can you do feature selection?
- Ans.
Feature selection can be done using techniques like filter methods, wrapper methods, and embedded methods.
Filter methods involve selecting features based on statistical measures like correlation, chi-squared test, etc.
Wrapper methods use a specific machine learning algorithm to evaluate the importance of features through iterative selection.
Embedded methods incorporate feature selection within the model training proces...
Skills evaluated in this interview
I applied via Naukri.com and was interviewed in Jan 2024. There were 2 interview rounds.
You can get the information and answer in Google
(3 Questions)
- Q1. Xg boost, naive Bayes algorithm, standard deviation formula and detailed information about that
- Q2. What is xg boost All about naive Bayes algorithm Standard deviations and the formula
- Q3. What is the Byes rules and there in deep
- Ans.
Bayes' rule is a fundamental concept in probability theory that allows us to update our beliefs based on new evidence.
Bayes' rule is named after Thomas Bayes, an 18th-century mathematician.
It is also known as Bayes' theorem or Bayes' law.
Bayes' rule calculates the probability of an event based on prior knowledge and new evidence.
It is commonly used in machine learning and statistical inference.
The formula for Bayes' ru...
Interview Preparation Tips
Skills evaluated in this interview
Not so tough and you will learn a lot of things that are new to you
The duration is about 90 minute
Selected
I applied via Recruitment Consulltant and was interviewed before Jul 2022. There were 4 interview rounds.
(2 Questions)
- Q1. About the assignment
- Q2. Writing assignment was asked
(1 Question)
- Q1. Softwares that i am aware of
- Ans.
I am aware of various e-learning authoring tools such as Articulate Storyline, Adobe Captivate, and Camtasia.
Articulate Storyline
Adobe Captivate
Camtasia
(1 Question)
- Q1. Html related questions were asked
Interview Preparation Tips
I applied via Recruitment Consultant and was interviewed before Aug 2020. There were 3 interview rounds.
Interview Questionnaire
1 Question
- Q1. Give a facilitation demo.
- Ans.
I would begin by introducing myself and the purpose of the facilitation. Then, I would engage the participants in an interactive activity to encourage participation and collaboration.
Introduce myself and the purpose of the facilitation
Engage participants in an interactive activity
Encourage participation and collaboration
Provide opportunities for reflection and feedback
Interview Preparation Tips
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Phenom Machine Learning Engineer Intern Interview Process
based on 1 interview
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