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Acies Global
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Acies Global Interview Questions and Answers for Freshers
Acies Global Interview Experiences for Freshers
1 interview found
Anonymous
1hr test with 5 sections, 60 questions, each section had separate timer. Questions were very easy and very basic
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I applied via Campus Placement and was interviewed before Sep 2020. There were 3 interview rounds.
Interview Questionnaire
1 Question
- Q1. Nothing much technical
Interview Preparation Tips
2. Fluency in English is important (depends on interview panel)
3. Clarity on what your talking about
Interview Preparation Tips
Experience: There were 3 rounds, All related to statistics and machine learning and whatever stuffs I had mentioned in my resume. HR round was not there. The partner of the firm just briefed me a bit about the company and asked me to relax without asking any questions in the third round.
Tips: Interview will be fun if you are thorough about your resume and it will be a cakewalk to you.
General Tips: Do's :
1. Prepare for Aptitude very seriously. Puzzles are important but aptitude is must.
2. Be thorough about everything you had specified in your resume
3. Be honest while creating your resume (It helps a lot)
Don'ts :
1. Don't get broken if you are not getting selected in Day 1 or 2 or so.
2. Don't over-prepare for case interviews, they are fairly simple.
Final Tips :
Be confident about yourself. Your attitude in the interview matters a lot. And don't lie even a bit in your resume. Many got selected with a poor resume than those with huge exaggerations.
College Name: IIT Kanpur
Interview Questionnaire
1 Question
- Q1. What PCA, Decision tree and computer vision
- Ans.
PCA is a dimensionality reduction technique, decision tree is a classification algorithm, and computer vision is a field of study focused on enabling computers to interpret and understand visual information.
PCA is used to reduce the number of variables in a dataset while retaining the most important information.
Decision trees are used to classify data based on a set of rules and conditions.
Computer vision involves usin...
Skills evaluated in this interview
Interview Questionnaire
1 Question
- Q1. Please tell me something about yourself.What is your experience? What are your goals and ambitions?Why We should hire you? Strengths and weaknesses etc.
I applied via Referral and was interviewed in Mar 2021. There were 4 interview rounds.
Interview Questionnaire
2 Questions
- Q1. What is data science
- Ans.
Data science is the field of extracting insights and knowledge from data using various techniques and tools.
Data science involves collecting, cleaning, and analyzing data to extract insights.
It uses various techniques such as machine learning, statistical modeling, and data visualization.
Data science is used in various fields such as finance, healthcare, and marketing.
Examples of data science applications include fraud...
- Q2. What is phyton and R
- Ans.
Python and R are programming languages commonly used in data science and statistical analysis.
Python is a general-purpose language with a large community and many libraries for data manipulation and machine learning.
R is a language specifically designed for statistical computing and graphics, with a wide range of packages for data analysis and visualization.
Both languages are popular choices for data scientists and hav...
Interview Preparation Tips
Skills evaluated in this interview
Interview Questionnaire
1 Question
- Q1. First Round: Basic Statistics, Basic Python Programming, Past Projects. Second Round: Past Projects, Questions from computer vision, NLP, SQL, Basic Python.
I applied via LinkedIn and was interviewed in Mar 2024. There was 1 interview round.
More about python and SQL coding
Interview Preparation Tips
- Python
- SQL
Good knowledge of different data types
(2 Questions)
- Q1. Number of Duplicate words in a string
- Ans.
Count the number of duplicate words in a string.
Split the string into words using a delimiter like space or punctuation.
Create a dictionary to store the count of each word.
Iterate through the words and increment the count in the dictionary.
Count the number of words with count greater than 1 as duplicates.
- Q2. Chunking in LLM
- Ans.
Chunking in LLM refers to breaking down text into smaller chunks for better processing by the language model.
Chunking helps improve the efficiency of the language model by breaking down large text inputs into smaller segments.
It can help the model better understand the context and relationships within the text.
Chunking is commonly used in natural language processing tasks such as text summarization and sentiment analys
Skills evaluated in this interview
I applied via Naukri.com and was interviewed in Jun 2022. There were 2 interview rounds.
Machine learning and artificial intillegence
Interview Preparation Tips
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