Accenture Learning & Development Specialist Interview Questions and Answers

Logical, Verbal, reasoning 90 mins

Q1. ML algorithms and Explain it?
Add your answer
Q2. Print even numbers in for loop?
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. ML algorithms, Live screen share coding
Add your answer

Q1. ML deployment, Cloud knowledge
Add your answer

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

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

Q1. Basics of DL and NLP , along with current projects
Add your answer

Q1. General scenario based on leadership and decision making
Add your answer