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posted on 24 Sep 2024
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I applied via Campus Placement and was interviewed in Nov 2024. There were 3 interview rounds.
There were verbal, non verbal, reasoning , English and maths questions
I worked on a project analyzing customer behavior using machine learning algorithms.
Used Python for data preprocessing and analysis
Implemented machine learning models such as decision trees and logistic regression
Performed feature engineering to improve model performance
Proficient in Python, R, and SQL with experience in data manipulation, visualization, and machine learning algorithms.
Proficient in Python for data analysis and machine learning tasks
Experience with R for statistical analysis and visualization
Knowledge of SQL for querying databases and extracting data
Familiarity with libraries such as Pandas, NumPy, Matplotlib, and Scikit-learn
I currently stay in an apartment in downtown area.
I stay in an apartment in downtown area
My current residence is in a city
I live close to my workplace
I am a data science enthusiast with a strong background in statistics and machine learning.
Background in statistics and machine learning
Passionate about data science
Experience with data analysis tools like Python and R
I applied via Naukri.com and was interviewed in Aug 2024. There was 1 interview round.
Fact is a statement that can be proven true or false, while figure is a numerical value or statistic.
Fact is a statement that can be verified or proven true or false.
Figure is a numerical value or statistic.
Facts are objective and can be verified through evidence or research.
Figures are quantitative data used to represent information.
Example: 'The sky is blue' is a fact, while 'The average temperature is 25 degrees Cel
Data modelling is the process of creating a visual representation of data to understand its structure, relationships, and patterns.
Data modelling involves identifying entities, attributes, and relationships in a dataset.
It helps in organizing data in a way that is easy to understand and analyze.
Common data modelling techniques include Entity-Relationship (ER) diagrams and UML diagrams.
Data modelling is essential for da...
I applied via Campus Placement
Basic DSA questions will be asked Leetcode Easy to medium
BERT is faster than LSTM due to its transformer architecture and parallel processing capabilities.
BERT utilizes transformer architecture which allows for parallel processing of words in a sentence, making it faster than LSTM which processes words sequentially.
BERT has been shown to outperform LSTM in various natural language processing tasks due to its ability to capture long-range dependencies more effectively.
For exa...
Multinomial Naive Bayes is a classification algorithm based on Bayes' theorem with the assumption of independence between features.
It is commonly used in text classification tasks, such as spam detection or sentiment analysis.
It is suitable for features that represent counts or frequencies, like word counts in text data.
It calculates the probability of each class given the input features and selects the class with the
I applied via Company Website and was interviewed in Jun 2024. There were 2 interview rounds.
2 coding questions asked in python
I applied via campus placement at Chennai Mathematical Institute, Chennai and was interviewed in Dec 2023. There was 1 interview round.
Large Language Models are advanced AI models that can generate human-like text based on input data.
Large Language Models use deep learning techniques to understand and generate text.
Examples include GPT-3 (Generative Pre-trained Transformer 3) and BERT (Bidirectional Encoder Representations from Transformers).
They are trained on vast amounts of text data to improve their language generation capabilities.
RAGs stands for Red, Amber, Green. It is a project management tool used to visually indicate the status of tasks or projects.
RAGs is commonly used in project management to quickly communicate the status of tasks or projects.
Red typically indicates tasks or projects that are behind schedule or at risk.
Amber signifies tasks or projects that are on track but may require attention.
Green represents tasks or projects that ar...
There is no one-size-fits-all answer as the best clustering algorithm depends on the specific dataset and goals.
The best clustering algorithm depends on the dataset characteristics such as size, dimensionality, and noise level.
K-means is popular for its simplicity and efficiency, but may not perform well on non-linear data.
DBSCAN is good for clusters of varying shapes and sizes, but may struggle with high-dimensional d...
I applied via Job Portal and was interviewed in Oct 2023. There were 4 interview rounds.
Coding test is important
Most important in coding test
Group discussion is share the projects many people one idea
posted on 16 Feb 2024
Good execellnt and well done
I applied via Monster and was interviewed in Feb 2022. There were 3 interview rounds.
Reasoning and arthematic
OOPs concepts are fundamental principles of object-oriented programming. Java was invented by James Gosling and C was invented by Dennis Ritchie.
OOPs concepts include encapsulation, inheritance, polymorphism, and abstraction.
Java was invented by James Gosling at Sun Microsystems in the early 1990s.
C was invented by Dennis Ritchie at Bell Labs in the early 1970s.
Flow charts and algorithms are used to represent the logic...
OOPs stands for Object-Oriented Programming. Strings are a sequence of characters. Arrays are a collection of elements. Operators are symbols used to perform operations.
OOPs is a programming paradigm that focuses on objects and their interactions.
Full form of OOPs is Object-Oriented Programming.
Strings are a sequence of characters, enclosed in quotes.
Arrays are a collection of elements of the same data type.
Operators a...
I am highly qualified and passionate about teaching, with a proven track record of success.
I have a strong educational background, with a PhD in my field of expertise.
I have several years of teaching experience, both at the undergraduate and graduate levels.
I am dedicated to student success and have received positive feedback from my previous students.
I am actively involved in research and have published papers in repu...
In 5 years, I see myself as an established Assistant Professor, leading research projects, publishing papers, and mentoring students.
Leading research projects in my field of expertise
Publishing papers in reputable journals
Mentoring and guiding students in their academic and research pursuits
Continuing professional development and staying updated with the latest advancements
Collaborating with colleagues and experts in t...
My strengths include strong communication skills, adaptability, and a passion for teaching. My weaknesses include a tendency to be overly critical of myself and a need for perfection.
Strength: Strong communication skills - I am able to effectively convey complex ideas and concepts to students, fostering a positive learning environment.
Strength: Adaptability - I am able to quickly adjust my teaching methods to meet the ...
I am a dedicated and experienced professional in the field of academia, specializing in [specific subject].
Ph.D. in [specific subject] from [university]
Published [number] research papers in renowned journals
Taught [number] courses at [university/institution]
Received [award/honor] for excellence in teaching
Currently conducting research on [specific topic]
My hobbies include reading, hiking, and playing the piano.
I enjoy reading a variety of genres, from fiction to non-fiction.
I love exploring nature and going on hikes to discover new trails.
Playing the piano is a great way for me to relax and express my creativity.
I also enjoy attending live music performances and concerts.
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HR Executive
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