Answer Posted / Madhulika Kumari

Supervised and unsupervised learning are two main categories of machine learning algorithms. Supervised learning uses labeled training data, where both input features and desired output labels are provided for each example. The goal is to learn a function that can map inputs to outputs based on the training examples. Common supervised learning algorithms include linear regression, logistic regression, support vector machines (SVM), and neural networks. In contrast, unsupervised learning focuses on finding patterns or structures in the data without explicit labels. Clustering and dimensionality reduction are common examples of unsupervised learning techniques.

Do you have research experience in machine learning?

73

What are standardization and normalisation? Give one advantage of each over the other?

74

Tell us do you have research experience in machine learning?

149

Tell me what are the last machine learning papers you've read?

209