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Group-108 Interview Questions and Answers

Updated 17 Jan 2025

Q1. Guestimates-"How many Ola cab runs in a day in Chennai"?

Ans.

It is difficult to provide an exact number, but there are likely thousands of Ola cab runs in Chennai each day.

  • The number of Ola cab runs in Chennai can vary depending on factors such as time of day, day of the week, and demand.

  • During peak hours, there may be a higher number of Ola cab runs as people commute to work or travel within the city.

  • On weekends or holidays, the number of Ola cab runs may increase due to leisure activities or tourism.

  • Ola's popularity and availability ...read more

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Q2. how would ypu plan a event calender

Ans.

To plan an event calendar, consider the purpose of the events, target audience, available resources, and desired outcomes.

  • Identify the purpose of the events (e.g. team building, training, celebrations)

  • Consider the target audience and their preferences (e.g. employees, clients, stakeholders)

  • Allocate resources such as budget, venue, speakers, and equipment

  • Set clear goals and desired outcomes for each event

  • Create a timeline with key milestones and deadlines

  • Promote the events thr...read more

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Q3. Longest sub array question in python.

Ans.

Find the longest subarray of strings in a given array.

  • Iterate through the array and keep track of the current subarray length.

  • Reset the subarray length when encountering a non-string element.

  • Return the length of the longest subarray found.

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Q4. Explain architecture of Efficient-nets

Ans.

EfficientNets are a family of convolutional neural networks that have been designed to achieve state-of-the-art accuracy with fewer parameters and FLOPS.

  • EfficientNets use a compound scaling method to balance network depth, width, and resolution for optimal performance.

  • They are based on a baseline network architecture called EfficientNet-B0, which is then scaled up to create larger models like EfficientNet-B1, EfficientNet-B2, and so on.

  • EfficientNets have been shown to outperf...read more

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Q5. Explain transformers architecture

Ans.

Transformers architecture is a deep learning model that uses self-attention mechanism to process sequential data.

  • Transformers consist of an encoder and a decoder, each composed of multiple layers of self-attention and feed-forward neural networks.

  • Self-attention mechanism allows the model to weigh the importance of different input tokens when making predictions.

  • Transformers have achieved state-of-the-art performance in various natural language processing tasks, such as machine...read more

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