Technical Interview Questions
Image, speech, and face detection Bioinformatics Market segmentation Manufacturing and inventory management Fraud detection, and so on When answering an interview question about the applications of machine learning, it’s important to provide a comprehensive overview while also highlighting specific examples or use cases. Here’s a structured response: Machine learning has found numerous applications across various … Read more
Model accuracy, a subset of model performance, is based on the model performance of an algorithm. Whereas, model performance is based on the datasets we feed as inputs to the algorithm. Model accuracy and model performance are both important metrics in evaluating the effectiveness of a machine learning model, but they represent different aspects of … Read more
Data acquisition Ground truth acquisition Cross validation technique Query type Scoring metric Significance test Relational evaluation techniques in artificial intelligence typically involve assessing the quality and performance of relational databases or knowledge bases. The components of relational evaluation techniques include: Accuracy: This measures how close the output of the system is to the true or … Read more
Regularization comes into the picture when a model is either overfit or underfit. It is basically used to minimize the error in a dataset. A new piece of information is fit into the dataset to avoid fitting issues. Regularization in machine learning is a technique used to prevent overfitting and improve the generalization ability of … Read more
Data collection Data preparation Choosing an appropriate model Training the dataset Evaluation Parameter tuning Predictions In an interview setting, when asked to list the steps involved in machine learning, you should provide a structured overview of the typical workflow involved in building and deploying machine learning models. Here are the key steps: Problem Definition: Clearly … Read more