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I was interviewed before Oct 2019.
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...
I expect challenging projects, opportunities for growth, collaborative team environment, and work-life balance.
Challenging projects that allow me to apply my data science skills and learn new techniques
Opportunities for growth and advancement within the company
Collaborative team environment where I can share ideas and work together towards common goals
Work-life balance to ensure I can perform at my best both profession
Topic was joining and calculating
I applied via Company Website and was interviewed in Jun 2023. There were 2 interview rounds.
I was asked to solve various problems (your typical algorithm and data structure subjects), as well as explain the various projects I worked on in my most recent position.
Divide candidates in a group of around 15 people, and put you through different activities such as role play exercises to measure your communication and team working skills.
posted on 6 May 2024
I applied via Recruitment Consulltant and was interviewed in Apr 2024. There was 1 interview round.
I applied via LinkedIn and was interviewed before Mar 2023. There were 2 interview rounds.
posted on 31 Mar 2024
I was interviewed in Oct 2023.
Based on topological sort
posted on 1 Jul 2024
Decision Trees are a popular machine learning algorithm used for classification and regression tasks.
Decision Trees are a tree-like structure where each internal node represents a feature or attribute, each branch represents a decision rule, and each leaf node represents the outcome.
They are easy to interpret and visualize, making them popular for exploratory data analysis.
Decision Trees can handle both numerical and c...
LLMs can be finetuned by adjusting hyperparameters, training on specific datasets, and using techniques like transfer learning.
Adjust hyperparameters such as learning rate, batch size, and number of layers to improve performance.
Train the LLM on domain-specific datasets to improve its understanding of specialized language.
Utilize transfer learning by starting with a pre-trained LLM model and fine-tuning it on a smaller...
posted on 13 Jun 2024
I applied via Company Website and was interviewed in May 2024. There was 1 interview round.
based on 4 reviews
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