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I appeared for an interview in Apr 2024.
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I applied via Recruitment Consulltant and was interviewed before Aug 2021. There was 1 interview round.
I have extensive knowledge of various tools and their practical applications in consulting projects.
Proficient in using tools like Microsoft Excel, PowerPoint, and Project for data analysis and project management
Familiar with CRM systems like Salesforce for client relationship management
Experience with industry-specific tools like Tableau for data visualization
Ability to adapt and learn new tools quickly to meet projec...
I applied via Approached by Company and was interviewed before Aug 2023. There were 3 interview rounds.
Isms overview refers to the study of various ideologies, beliefs, and systems of thought.
Isms refer to various ideologies and beliefs such as capitalism, socialism, feminism, etc.
They are often used to categorize and analyze different political, social, and philosophical movements.
Studying isms helps in understanding the underlying principles and values that shape societies and individuals.
Examples include Marxism, exi...
I am very comfortable conducting training sessions and have experience in delivering engaging and informative sessions.
I have experience in conducting training sessions for new employees on company policies and procedures.
I am confident in my ability to communicate effectively and engage with participants during training sessions.
I have received positive feedback from previous training sessions I have conducted.
I am co...
I applied via Recruitment Consultant
I applied via Approached by Company and was interviewed in Feb 2023. There were 2 interview rounds.
I applied via LinkedIn and was interviewed in Nov 2024. There were 2 interview rounds.
I appeared for an interview in Dec 2024.
Bagging and boosting are ensemble learning techniques used to improve the performance of machine learning models by combining multiple weak learners.
Bagging (Bootstrap Aggregating) involves training multiple models independently on different subsets of the training data and then combining their predictions through averaging or voting.
Boosting involves training multiple models sequentially, where each subsequent model c...
Overfitting is when a model learns the training data too well, leading to poor performance on new, unseen data.
Overfitting occurs when a model is too complex and captures noise in the training data.
It can be mitigated by using techniques like cross-validation, regularization, and early stopping.
Examples of overfitting include a decision tree with too many branches or a neural network with too many hidden layers.
Discrete variables can only take specific values, while continuous variables can take any value within a range.
Discrete variables are countable and have distinct values, such as number of students in a class.
Continuous variables can take any value within a range, such as height or weight.
Discrete variables are often represented by integers, while continuous variables are represented by real numbers.
I applied via Approached by Company and was interviewed in Nov 2024. There were 2 interview rounds.
Coding test is related to my tech skills only.
based on 2 interview experiences
based on 3 reviews
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