Text summarization, the creation of entirely new pieces of text, and the prediction of the next word like Google’s auto-fill, to name a few.
Representation learning is a very important aspect of machine learning which automatically discovers the feature patterns in the data.
In swarm learning, a global system is divided into agents with their environment. And interaction behaviour of the agents leads to the global solution behaviour. In terms of neural networks,
Measuring the performance of any machine learning model is very important, not only from the technical point of view but also from the business perspective.
In the last few years, we have seen that self-supervised learning methods are emerging rapidly. It can also be noticed that models using self-supervised learning
Extrapolation is a sort of estimation of a variable’s value beyond the initial observation range based on its relationship with another variable.
We can simply apply the dimension reduction by choosing the random projection of the data. Locally-Linear Embedding is a approach for dimension reduction
Pix2seq is a new approach which is designed in intuition which states that if a neural network is already trained about the where and what the objects are. We just need to train the network to read them out
Federated learning is a method that stores only learnt models on a server in order to protect data privacy.
When a product owner or service provider wants to know the feedback of the users, sentiment analysis gives a strong indication of how the users are satisfied with the product or service.
Machine learning is the scientific study of algorithms and statistical models to perform a specific task effectively without using explicit instructions. Machine learning algorithms include
Generalization and Regularization are two often terms that have the most significant role when you aim to build a robust machine learning model.
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