Adagrad AI Interview Questions, Process, and Tips

Implement a model improvement using a C++ API of Pytorch.

Q1. Rotate an image in your choice of language
Ans. 
To rotate an image in Python, use the Pillow library's rotate() method.
• Import the Image module from the Pillow library

• Open the image using the open() method

• Use the rotate() method to rotate the image by the desired angle

• Save the rotated image using the save() method
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Q2. A breadth first search problem
Ans. 
Breadth first search problem
• BFS is a graph traversal algorithm that visits all the vertices of a graph in breadth-first order

• It uses a queue to keep track of the nodes to be visited next

• BFS can be used to find the shortest path between two nodes in an unweighted graph
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Q1. Questions based on my past jobs, past experience and behaviour.
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Some OpenCV problems

Q1. Why are activation functions used
Ans. 
Activation functions are used to introduce non-linearity into neural networks, allowing them to learn complex patterns and relationships.
• Activation functions help neural networks to learn complex patterns and relationships by introducing non-linearity.

• They help in controlling the output of a neuron, ensuring that it falls within a desired range.

• Common activation functions include ReLU, Sigmoid, Tanh, and Leaky ReLU.

• Wit...read more
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Q2. What is learning rate
Ans. 
Learning rate is a hyperparameter that controls how much we are adjusting the weights of our network with respect to the loss gradient.
• Learning rate determines the size of the steps taken during optimization.

• A high learning rate can cause the model to overshoot the optimal weights, while a low learning rate can result in slow convergence.

• Common learning rate values are 0.1, 0.01, 0.001, etc.

• Learning rate can be adjuste...read more
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Q1. What is the difference between CNN and RNN
Ans. 
CNN is used for image recognition while RNN is used for sequence data like text or speech.
• CNN is Convolutional Neural Network, used for image recognition tasks.

• RNN is Recurrent Neural Network, used for sequence data like text or speech.

• CNN has convolutional layers for feature extraction, while RNN has recurrent connections for sequential data processing.

• CNN is good at capturing spatial dependencies in data, while RNN i...read more
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Q2. Is Logloss function differentiable
Ans. 
Yes, Logloss function is differentiable.
• Logloss function is differentiable as it is a smooth and continuous function.

• The derivative of Logloss function can be calculated using calculus.

• Differentiability is important for optimization algorithms like gradient descent to converge smoothly.

• Example: The derivative of Logloss function for binary classification is (predicted probability - actual label).
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Q3. Questions on YOLO models
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