Rapid Fire on Machine Learning

Pattern Recognition can be used in Computer Vision Speech Recognition Data Mining Statistics Informal Retrieval Bio-Informatics Pattern recognition is a fundamental concept that finds applications in various fields. Here are some key areas where pattern recognition is commonly used: Computer Vision: Pattern recognition plays a crucial role in computer vision tasks such as object detection, … Read more

In Naïve Bayes classifier will converge quicker than discriminative models like logistic regression, so you need less training data. The main advantage is that it can’t learn interactions between features. In a machine learning interview, when asked about the advantages of Naive Bayes classifier, you can mention several key points: Simplicity and Efficiency: Naive Bayes … Read more

A classifier in a Machine Learning is a system that inputs a vector of discrete or continuous feature values and outputs a single discrete value, the class. In machine learning, a classifier is a model that is trained to classify input data into predefined categories or classes based on certain features or attributes. The goal … Read more

Designing and developing algorithms according to the behaviours based on empirical data are known as Machine Learning. While artificial intelligence in addition to machine learning, it also covers other aspects like knowledge representation, natural language processing, planning, robotics etc. In the context of a machine learning interview question, the difference between “artificial learning” and “machine … Read more

Machine learning in where mathematical foundations is independent of any particular classifier or learning algorithm is referred as algorithm independent machine learning? Algorithm-independent machine learning refers to the capability of a machine learning model to be trained and operate effectively regardless of the specific algorithm used for training. In other words, the performance of the … Read more