Accenture Senior Data Scientist Interview Questions and Answers

Big data refers to large, complex datasets that traditional data processing software cannot manage efficiently.

• Volume: Refers to the vast amounts of data generated daily, e.g., social media posts, sensor data.

• Velocity: The speed at which data is generated and processed, e.g., real-time data from IoT devices.

• Variety: The different types of data, including structured, semi-structured, and unstructured data, e.g., te...read more

Use techniques like regularization, feature selection, cross-validation, and data augmentation.

• Utilize regularization techniques like Lasso or Ridge regression to prevent overfitting.

• Perform feature selection to focus on the most important variables and reduce noise.

• Use cross-validation to assess model performance and generalizability.

• Consider data augmentation techniques like synthetic data generation or bootstra...read more

Lambda function is an anonymous function in Python that can take any number of arguments and can only have one expression.

• Lambda functions are defined using the keyword 'lambda'.

• They are commonly used with built-in functions like filter(), map(), and reduce().

• Lambda functions can be used to create small, throwaway functions that are not needed elsewhere in the code.

• They are often used to write more concise and rea...read more

BERT is a bidirectional transformer model for pre-training language representations, while GPT is a generative model.

• BERT is a pre-training model that learns contextual representations of words by considering both left and right context.

• GPT is a generative model that uses a transformer decoder to generate text based on the context.

• BERT is bidirectional, meaning it can understand the context of a word by looking at...read more

AI simulates human intelligence in machines; ML enables them to learn from data and improve over time.

• AI (Artificial Intelligence) refers to the simulation of human intelligence in machines.

• ML (Machine Learning) is a subset of AI that focuses on algorithms that learn from data.

• Examples of AI include virtual assistants like Siri and Alexa.

• Examples of ML include recommendation systems like those used by Netflix and ...read more