Rapid Fire on Machine Learning

Classifications Speech recognition Regression Predict time series Annotate strings The function of supervised learning is to train a model to learn the mapping between input data and corresponding output labels based on a labeled dataset. In supervised learning, the algorithm is provided with a dataset consisting of input-output pairs, where the inputs are features or … Read more

Find clusters of the data Find low-dimensional representations of the data Find interesting directions in data Interesting coordinates and correlations Find novel observations/ database cleaning In machine learning, unsupervised learning is a type of learning where the algorithm learns to find patterns and structures in data without explicit guidance or labeled responses. Unlike supervised learning, … Read more

Artificial Intelligence Rule based inference In the context of a machine learning interview question asking “What is not Machine Learning?”, the correct answer would typically involve distinguishing between tasks or techniques that do not fall under the umbrella of machine learning. Here’s a succinct response: “Machine learning involves the development of algorithms and models that … Read more

The different approaches in Machine Learning are Concept Vs Classification Learning Symbolic Vs Statistical Learning Inductive Vs Analytical Learning In a machine learning interview, when asked about various approaches for machine learning, you can provide a comprehensive list that covers different categories of machine learning algorithms and techniques. Here’s a breakdown: Supervised Learning: Classification: Predicting … Read more

In various areas of information science like machine learning, a set of data is used to discover the potentially predictive relationship known as ‘Training Set’. Training set is an examples given to the learner, while Test set is used to test the accuracy of the hypotheses generated by the learner, and it is the set … Read more