Answer:
Nomad means Option C: People with no permanent home.
Explanation:
Nomads are the people who do not have a home that is permanent. They wander from place to place for food and shelter. They also depend on climate and availability of plants and animals for their movement.
Aryans were the nomadic tribes who came from the north of the 'Caucasus Mountains'. These Aryan tribes migrated to India independently and gradually they settled in Indus Valley. Here they brought their culture, language and custom. As they began to settle, they stopped living as 'nomads'.
Answer:
Magna Carta movement in 1215.
Explanation:
a) The Magna Carta movement in 1215 leads to the advancement of human rights. This carta movement gave people new rights and made the king subject to the law.
b) The limitation of human rights made by the government itself in order to stop instability in the society and keep the humans in control. There is no such movement is present on the internet.
c) The main difference between these two movements are that one movement started to get human rights while on the other hand, the second movement initiated to limit the range of human rights because unlimited rights can cause big problem in the society.
A multi-task learning-based framework that utilizes a combination of self-supervised and supervised pre-training tasks to learn a generic document representation. They design the network architecture and the pre-training tasks to incorporate the multi-modal document information across text, layout, and image dimensions and allow the network to work with multi-page documents.
What do you mean by multi-task learning?
Multi-task learning, on the other hand, is a machine learning approach in which we try to learn multiple tasks simultaneously, optimizing multiple loss functions at once. Rather than training independent models for each task, we allow a single model to learn to complete all of the tasks at once.
How does multi-task learning work?
Multi-task learning is a sub field of machine learning in which multiple tasks are simultaneously learned by a shared model. Such approaches offer advantages like improved data efficiency, reduced overfitting through shared representations, and fast learning by leveraging auxiliary information
What is a multi modal?
Multi modal machine learning aims to build models that can process and relate information from multiple modalities. It is a vibrant multi-disciplinary field of increasing importance and with extraordinary potential.
Learn more about multi model :
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I believe it is b i’m not a 100% sure