Data science and analytics are rapidly growing fields, and landing a job at a top tech company like Yahoo can be a significant career achievement. To help you prepare, we’ve compiled a list of likely interview questions along with model answers that you might encounter during a data science and analytics interview at Yahoo. Let’s break down the core areas and explore the types of questions you should be ready to answer.
Table of Contents
ML and DL Interview Questions
Question: What is overfitting in machine learning?
Answer: Overfitting occurs when a model learns the detail and noise in the training data to the extent that it negatively impacts the performance of the model on new data. This means the model is too complex, capturing patterns that do not generalize to unseen data.
Question: Can you explain the difference between supervised and unsupervised learning?
Answer: Supervised learning involves training a model on a labeled dataset, meaning each training instance has an associated output label. In unsupervised learning, the training data is unlabeled, and the goal is to identify inherent patterns or groupings in the data, such as clustering or association.
Question: What is the role of the activation function in a neural network?
Answer: The activation function in a neural network introduces non-linearities into the model, enabling it to learn more complex patterns in the data. Without non-linear activation functions, the network would essentially function as a linear regressor, limiting its ability to solve non-linear problems.
Question: How does dropout help in reducing overfitting in neural networks?
Answer: Dropout is a regularization technique where randomly selected neurons are ignored during training. This helps in reducing overfitting by making the network less sensitive to the specific weights of neurons, thereby enhancing the network’s ability to generalize better to new data.
Question: What is gradient descent, and how does it work?
Answer: Gradient descent is an optimization algorithm used to minimize the cost function in machine learning and deep learning models. It works by iteratively adjusting the parameters (weights) of the model, moving in the direction of the steepest descent as defined by the negative of the gradient.
Question: Explain the concept of “backpropagation” in training neural networks.
Answer: Backpropagation is a training algorithm used for neural networks that calculates the gradient of the loss function of the network concerning its weights. It works by propagating the error backward through the network, from the output towards the input layer, thereby updating the weights to minimize the loss.
Database and SQL Interview Questions
Question: What is a primary key in a database?
Answer: A primary key is a field in a table that uniquely identifies each row/record in that table. Primary keys must contain unique values, and they cannot contain NULL values. A table can have only one primary key, which may consist of single or multiple fields.
Question: Explain the difference between DELETE and TRUNCATE commands in SQL.
Answer: The DELETE command is used to remove rows from a table based on a specific condition provided by the WHERE clause or remove all rows if no condition is specified. It is a DML command and can be rolled back. On the other hand, TRUNCATE removes all rows from a table, resets the table identity to the initial value if it has an auto-increment column, and cannot be rolled back. It is a DDL command.
Question: What are joins in SQL, and can you name the different types?
Answer: Joins in SQL are used to combine rows from two or more tables based on a related column between them. The different types of joins include INNER JOIN, LEFT OUTER JOIN, RIGHT OUTER JOIN, FULL OUTER JOIN, and CROSS JOIN.
Question: Can you explain what a foreign key is and its purpose in a database?
Answer: A foreign key is a column or group of columns in a relational database table that provides a link between data in two tables. It acts as a cross-reference between tables because it references the primary key of another table, thereby establishing a relationship between the tables.
Question: What is normalization? Why is it important?
Answer: Normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves dividing large tables into smaller tables and defining relationships between them according to rules designed to safeguard the data and make the database more efficient (e.g., 1NF, 2NF, 3NF).
Question: How do you improve the performance of a database query?
Answer: Improving database query performance can involve several strategies such as indexing to speed up data retrieval, optimizing SQL queries by eliminating unnecessary columns, using joins instead of subqueries where appropriate, and ensuring the database statistics are up-to-date for optimal execution path selection by the query planner.
Probability Interview Questions
Question: What is probability?
Answer: Probability measures the likelihood of a specific event occurring among all possible outcomes. It is quantified as a number between 0 and 1, where 0 indicates impossibility and 1 indicates certainty.
Question: Can you explain what a probability distribution is?
Answer: A probability distribution describes how the values of a random variable are distributed. It defines the probabilities of occurrence of different possible outcomes in an experiment. For discrete variables, it is expressed as a probability mass function, and for continuous variables, it is expressed as a probability density function.
Question: What is the difference between independent and dependent events?
Answer: Independent events are those where the occurrence of one event does not affect the occurrence of another event. In contrast, dependent events are those where the occurrence of one event affects the occurrence of another. For example, drawing cards from a deck without replacement is a dependent event because each draw changes the probabilities of the following draws.
Question: Explain the Law of Large Numbers.
Answer: The Law of Large Numbers states that as a sample size grows, its mean gets closer to the average of the whole population. In a gambling context, this might mean that while a player could be ahead in the short term, the casino will win in the long term because the average outcome across many bets will favor the house.
Question: What is a p-value?
Answer: A p-value is the probability of observing test results at least as extreme as the results observed, under the assumption that the null hypothesis is correct. It is used as a tool in statistical hypothesis testing to measure the strength of the evidence against the null hypothesis and in favor of the alternative hypothesis.
Question: How would you use probability theory in data analysis at Yahoo?
In data analysis at Yahoo, probability theory could be used to model and predict user behaviors, evaluate A/B testing results, detect anomalies in traffic data, optimize algorithms for search and content recommendation, and manage risks in financial and business decisions.
Data Structure and Application Design Interview Questions
Question: What are the different types of data structures and their uses?
Answer: Data structures are broadly divided into linear and non-linear structures. Linear structures include arrays, linked lists, stacks, and queues, which are primarily used for collecting and organizing data sequentially. Non-linear structures include trees and graphs, which are used for representing hierarchical relationships or networked connections.
Question: Can you explain the difference between an array and a linked list?
Answer: An array is a collection of elements identified by an index, stored contiguously in memory, which allows for fast random access but slow insertions and deletions. A linked list, on the other hand, consists of nodes that are not stored in contiguous memory, each pointing to the next node in sequence, which facilitates easier insertions and deletions but slower random access.
Question: What is a hash table and how does it work?
Answer: A hash table is a data structure that implements an associative array, a structure that can map keys to values. It uses a hash function to compute an index into an array of buckets or slots, from which the desired value can be found. This mechanism allows for efficient lookup, insert, and delete operations.
Question: Explain the concept of a binary tree and its types.
Answer: A binary tree is a tree data structure in which each node has at most two children referred to as the left child and the right child. Types of binary trees include binary search trees (BST), where each node follows the left < root < right order; AVL trees, which are height-balanced; and Red-Black trees, which are balanced by ensuring specific properties.
Question: How would you design a URL shortening service like bit.ly?
Answer: Designing a URL shortening service involves using a hash function to convert a long URL into a shorter, unique identifier, storing this mapping in a database for persistent storage. The application should handle potential hash collisions, provide redirection from the shortened URL to the original URL, and possibly offer features like analytics on the URLs.
Question: What are microservices and how would they be used in a project at Yahoo?
Answer: Microservices architecture breaks down an application into smaller, independent services that perform specific functions. This design enhances scalability and maintainability. At Yahoo, microservices could be used to handle different aspects of the platform such as handling user profiles, ad services, content feeds, and notifications independently.
Question: Explain the importance of API design in web services.
Answer: API design is crucial as it dictates how different software components interact. A well-designed API ensures security, ease of use, and scalability of applications. It should have clear and concise endpoints, use appropriate HTTP methods, provide meaningful error messages, and be versioned to handle changes without breaking existing clients.
Question: Discuss the role of load balancers in system design.
Answer: Load balancers distribute incoming network traffic across multiple servers to ensure no single server bears too much demand. By spreading the load, load balancers increase the availability and reliability of applications, prevent server overloads, and ensure smoother handling of requests, essential for maintaining performance during peak traffic times.
General Behavioral Interview Questions
Que: Tell me about yourself.
Que: Do you have any questions for me?
Que: What are your Salary Expectation
Que: How would you describe a Gaussian distribution to someone who has never heard about it?
Conclusion
Preparing for an interview at Yahoo requires a balanced approach, including understanding fundamental concepts, technical details, practical applications, and the ability to communicate effectively. Remember to tailor your responses based on the job role and the specific requirements mentioned in the job description. Good luck!
