Archives for semi-supervised
Developers are constantly enhancing artificial intelligence capability by leveraging various machine learning methodologies like supervised, unsupervised, and reinforcement learning. More recently, Facebook used supervised learning for state-of-the-art image and video classification. They call their new approach as semi-weak supervision, where the firm combined semi-supervised learning and weakly supervised learning to achieve a new benchmark in…
The post Is Semi-Supervised Learning The Future Of Image & Video Classification? appeared first on Analytics India Magazine.
Semi-weakly supervised learning is a product of combining the merits of semi-supervised and weakly supervised learning. The goal here is to create efficient classification models. To test this, Facebook AI has used a teacher-student model training paradigm and billion-scale weakly supervised data sets. An example of a weakly supervised data set can be hashtags associated…
The post How To Do Machine Learning When Data Is Unlabelled appeared first on Analytics India Magazine.
Semi-weakly supervised learning is a product of combining the merits of semi-supervised and weakly supervised learning. The goal here is to create efficient classification models. To test this, Facebook AI has used a teacher-student model training paradigm and billion-scale weakly supervised data sets. An example of a weakly supervised data set can be hashtags associated…
The post How To Do Machine Learning When Data Is Unlabelled appeared first on Analytics India Magazine.
Data augmentation is often limited to supervised learning, in which labels are required to transfer from original examples to augmented ones. Augmentation provides a steady but limited performance boost. This is because of the fact that they have been applied to a set of labelled examples which is usually of a small size. To overcome…
The post How Unsupervised Data Augmentation Can Improve NLP And Vision Tasks appeared first on Analytics India Magazine.