Here is a set of frequently asked interview questions on generative AI. What is generative AI, and how does it differ from other types of AI? Generative AI focuses on creating new data, such as images, texts, or sounds, that resemble real data. Unlike other AI, which might classify or predict, generative AI produces entirely …
We have published seven modules of interview questions in machine learning and answers so far on this website. This is yet another addition to the series of discussion on frequently asked questions in machine learning job roles. Whether stochastic gradient descent or gradient descent is computationally complex? Gradient descent is computationally complex. After identifying a …
This is another addition to the series of machine learning (ML) interview questions and answers that have been published on this website. What are Sigmoid function and softmax functions? Explain the difference Sigmoid and softmax functions are functions used for the classification tasks in machine learning and deep learning. Both Sigmoid function and softmax function …
This article discusses a couple of machine learning (ML) interview questions asked frequently in data science related job roles. When should we prefer ridge regression over lasso? Explain with reason Ridge regression is a regression in which we use L2 regularization to give a penalty to the loss function to reduce loss in the optimization …
This blog is part 5 of machine learning interview questions and answers series. Previous blog article and be found here. What is the need of cross validation in machine learning modeling? Cross validation is used to better utilize the input data to ensure the model performance. The input data will be divided into many subsets …
This is one among the series of frequently asked interview questions in machine learning. Concepts are demonstrated with schematics wherever necessary Differentiate between local optimization and global optimization Optimization is a process of assigning a set of inputs to an objective function that can extract the best possible output from the objective function. Local optimization …
The article discusses interview questions asked in many machine learning job roles Explain label encoding and one hot encoding, Explain how the dimensionality of a dataset is affected with these methods in machine learning Machine learning algorithms can understand only numbers. Often, the dataset consists of categorical and numerical features. We need to convert the …
This article is one among the series of discussions on interview questions frequently asked in machine learning job roles Explain the concept confusion matrix in machine learning? Confusion matrix is a table displaying a summary of prediction results of a classification problem. Measuring accuracy of a model alone can be misleading in cases where the …
This is one among a series of frequently asked interview questions in machine learning published in this website Explain the terms Artificial Intelligence, Machine Learning, Deep Learning, and Reinforcement Learning? Artificial Intelligence (AI) is the domain of intelligent machines which can think rationally and act rationally. It uses algorithms to enable problem solving with robust …