Aganitha Cognitive Solutions Machine Learning Engineer Interview Questions, Process, and Tips

Q1. What is evaluation Matrix for classification
Ans. 
Evaluation metrics for classification are used to assess the performance of a classification model.
• Common evaluation metrics include accuracy, precision, recall, F1 score, and ROC-AUC.

• Accuracy measures the proportion of correctly classified instances out of the total instances.

• Precision measures the proportion of true positive predictions out of all positive predictions.

• Recall measures the proportion of true positive p...read more
Answered by AI
Add your answer
Q2. What L1 and L2 regression
Ans. 
L1 and L2 regression are regularization techniques used in machine learning to prevent overfitting.
• L1 regression adds a penalty equivalent to the absolute value of the magnitude of coefficients.

• L2 regression adds a penalty equivalent to the square of the magnitude of coefficients.

• L1 regularization can lead to sparse models, while L2 regularization tends to shrink coefficients towards zero.

• L1 regularization is also know...read more
Answered by AI
Add your answer
Q3. Explain random forest algorithm
Ans. 
Random forest is an ensemble learning algorithm that builds multiple decision trees and combines their predictions.
• Random forest creates multiple decision trees using bootstrapping and feature randomization.

• Each tree in the random forest is trained on a subset of the data and features.

• The final prediction is made by averaging the predictions of all the trees (regression) or taking a majority vote (classification).
Answered by AI
Add your answer

Q1. Tell me about self
Ans. 
I am a dedicated and passionate Machine Learning Engineer with a strong background in computer science and data analysis.
• Experienced in developing machine learning models for various applications

• Proficient in programming languages such as Python, R, and Java

• Skilled in data preprocessing, feature engineering, and model evaluation

• Strong understanding of algorithms and statistical concepts

• Excellent problem-solving and ana
Answered by AI
Add your answer
Q2. Questions about salary discuss
Add your answer

Q1. Basic Stats questions
Add your answer
Q2. Basic ML questions
Add your answer

Q1. Started with basic os or network fundamentals like analyzing a core dump, handling tcp packet loss, difference between rest api and grpc etc. Then, from ML started with basic questions like bias variance t...read more
Add your answer

Q1. Difference between bias and variance
Ans. 
Bias is error due to overly simplistic assumptions, variance is error due to overly complex models.
• Bias is error introduced by approximating a real-world problem, leading to underfitting.

• Variance is error introduced by modeling the noise in the training data, leading to overfitting.

• High bias can cause a model to miss relevant relationships between features and target variable.

• High variance can cause a model to be overl...read more
Answered by AI
Add your answer
Q2. What’s is Learning rate
Ans. 
Learning rate is a hyperparameter that controls how much we are adjusting the weights of our network with respect to the loss gradient.
• Learning rate determines the size of the steps taken during optimization.

• A high learning rate can cause the model to converge too quickly and potentially miss the optimal solution.

• A low learning rate can cause the model to take a long time to converge or get stuck in a local minimum.

• Com...read more
Answered by AI
Add your answer

Problem solving skills

Logical reasoning numerical reasoning abstract reasoning verbal reasoning

Q1. Self introduction
Add your answer
Q2. Family background
Add your answer
Q3. Salary expectation
Add your answer

Q1. Explain the latest project you worked on in terms of your role in it.
Add your answer

Q1. Behavioral and situational questions
Add your answer

Q1. ML algorithms, Live screen share coding
Add your answer

Q1. ML deployment, Cloud knowledge
Add your answer

Machine learning - Code K-Means

Machine Learning - Code Neural Network

Q1. Machine Learning Fundamentals
Add your answer
Q2. Python Advanced
Add your answer

Q1. Why this company
Add your answer