United Airlines Interview Questions, Process, and Tips

Q1. Why are you leaving your current job
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Q2. Are you willing to relocate
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Q1. Explain the types of basic joins
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Q1. How LLM use neural network
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LLM can use neural networks for tasks such as natural language processing, image recognition, and predictive analytics.
• Neural networks can be used in LLM for natural language processing tasks such as sentiment analysis, text generation, and language translation.

• LLM can utilize neural networks for image recognition tasks like object detection, facial recognition, and image classification.

• Neural networks can also be appl...read more
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Q2. How back propagation in NN work
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Back propagation is a method used to train neural networks by adjusting the weights based on the error calculated during the forward pass.
• Back propagation involves calculating the error between the predicted output and the actual output.

• The error is then propagated backwards through the network to adjust the weights using gradient descent.

• This process is repeated iteratively until the network's performance improves.

• Exa...read more
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Q1. About me and my experience
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Q2. Experience with cloud
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Python, sql were asked, 1st round was resume based round

1 hour with questions on medium level .net core , web api's and react as frontend.

Q1. How custom Middleware is created with code example?
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Q2. DI lifecycle and its use with past experience on any of yours project?
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Q1. Salary expectations?
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Q2. Explained about benefits and variables with the job level.
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Q1. How regularisation works in random forest
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Regularisation in random forest helps prevent overfitting by controlling the complexity of the model.
• Regularisation in random forest is achieved by limiting the depth of the trees in the forest.

• It helps prevent overfitting by reducing the complexity of the model and improving generalization.

• Regularisation parameters like max_depth, min_samples_split, and min_samples_leaf can be tuned to control the complexity of the mo
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