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How would you construct a parser to handle strings with deeply nested brackets?

How does Gradient Descent interplay with deep learning models during the training phase?

How would you describe regularization in the context of machine learning ?

What's your approach to implementing a recursion-based function for the nth Fibonacci term?

What are the key differences between RNNs and LSTMs you could point out?

Create a chat application with end-to-end encryption like WhatsApp.

How to generate a normal distribution of 1000 data points with a set mean and variance in R, complete a statistical summary with explanation, and create a density plot, and then perform these steps in Python using the Codility editor?

Could you explain how the K-means and Expectation-Maximization (EM) algorithm differ in their approaches?

Could you explain the essential phases of backpropagation used in neural network training?

Can you elaborate on the difficulties in managing and optimizing models with several layers?