Fego Associate Data Scientist 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
Answered by AI
Add your answer
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
Answered by AI
Add your answer
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
Answered by AI
Add your answer

How to improve the ETA estimation for Food delivery apps and how to improve customer retention and engagment