Fego Interview Questions and Answers

Q1. What are RNNs ?
Ans. 
RNNs are Recurrent Neural Networks, a type of neural network designed to handle sequential data by retaining memory of previous inputs.
• RNNs have loops that allow information to persist, making them suitable for tasks like speech recognition and language modeling.

• They can process inputs of varying lengths and are capable of learning patterns in sequences.

• Examples of RNN variants include LSTM (Long Short-Term Memory) and
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Q2. Explain GRUs and LSTMs
Ans. 
GRUs and LSTMs are types of recurrent neural networks (RNNs) used for sequential data processing.
• GRUs (Gated Recurrent Units) are a simplified version of LSTMs with fewer gates.

• LSTMs (Long Short-Term Memory) are a type of RNN that can learn long-term dependencies.

• Both GRUs and LSTMs are designed to address the vanishing gradient problem in traditional RNNs.

• GRUs have reset and update gates, while LSTMs have input, outpu...read more
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Q3. Explain about Gradient Decay
Ans. 
Gradient decay is a technique used in optimization algorithms to gradually reduce the learning rate over time.
• Gradient decay helps prevent overshooting the minimum point in the loss function by slowing down the learning rate as the optimization process progresses.

• Common methods of gradient decay include exponential decay, polynomial decay, and step decay.

• Exponential decay reduces the learning rate exponentially over ti...read more
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How to improve the ETA estimation for Food delivery apps and how to improve customer retention and engagment

Go-to-market strategy for one of the products

Q1. Complete walk through of the assignment
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Q1. Previous experience in B2B SaaS / Fintech
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