Sony India Software Center Interview Questions, Process, and Tips

Project architecture refers to the high-level structure of a software system, including components, relationships, and interactions.

• Project architecture defines how different components of a software system interact with each other.

• It includes the design decisions related to technologies, frameworks, databases, and communication protocols.

• Common architectural patterns include MVC, microservices, and layered architectur...read more

Find unique elements in a given string

• Iterate through each character in the string

• Use a hash set to keep track of unique characters

• If a character is already in the set, it is not unique

• Return the set of unique characters as an array of strings

The POST method in Rest Assured is used to send data to a server to create a new resource.

• Use the given() method to set the base URI and path

• Create a request specification using the request() method

• Set the request body using the body() method

• Specify the content type using the contentType() method

• Send the POST request using the post() method

• Validate the response using assertions

Objectness loss is a loss function used in object detection models to penalize incorrect localization of objects.

• Objectness loss helps in determining how well the model localizes objects in an image.

• It penalizes the model for predicting bounding boxes that do not contain the object of interest.

• Commonly used in models like YOLO (You Only Look Once) for object detection tasks.

Vanishing gradient occurs when gradients become very small during backpropagation, leading to slow learning or stuck in local minima.

• Vanishing gradient is a common issue in deep neural networks, especially in deep architectures like RNNs.

• It occurs when the gradients of the loss function with respect to the weights become very small, making weight updates negligible.

• To avoid vanishing gradient, one can use activation fu...read more

Yes, embeddings can be created from base using techniques like Word2Vec, GloVe, or FastText. Text embeddings can also be created from pretrained models like BERT or Word2Vec.

• Use techniques like Word2Vec, GloVe, or FastText to create embeddings from base data

• Pretrained models like BERT or Word2Vec can be used to create text embeddings

• Fine-tuning pretrained models can also be done to create custom text embeddings