This may not be for everyone (it isn't for me), but for most people a billboard would be the correct answer.
B. false . <span>The understanding between the three powers, supplemented by agreements with </span>Japan<span> and Portugal, was a powerful counterweight to the </span>Triple<span> Alliance of Germany, Austria-Hungary, and </span>Italy. However,Italy<span> did not side with Germany and Austria during World War I and </span>joined<span> the </span>Entente<span> instead </span>in the<span>Treaty of London (1915).</span>
Answer:
Intergenerational mobility.
Explanation:
Intergenerational mobility refers to the changes in social status between different generations within the same family, this type of mobility permits new generations to have better opportunities than the ones that their ancestors had and change their social status.
In this example Carlos' grandfather was an agricultural worker, Carlos' father worked as a clerk and because of their efforts, Carlos' is now able to graduate from college and medical school. We can see how Carlos' family has gone through changes in social status thanks to the efforts and opportunities they created.
Thus, this is an example of intergenerational mobility.
I think the answer would be C. y
dzmitry bahdanau, kyunghyun cho, and yoshua bengio. 2014. neural machine translation by jointly learning to align and
Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance.
The models proposed as of late for brain machine interpretation frequently have a place with a group of encoder-decoders and comprises of an encoder that encodes a source sentence into a fixed-length vector from which a decoder creates an interpretation.
In this paper, we guess that the utilization of a fixed-length vector is a bottleneck in working on the exhibition of this essential encoder-decoder engineering, and propose to broaden this by permitting a model to naturally (delicate )look for parts of a source sentence that are pertinent to anticipating an objective word, without shaping these parts as a hard section unequivocally.
With this new methodology, we accomplish an interpretation execution equivalent to the current cutting edge state put together framework with respect to the undertaking of English-to-French interpretation. Moreover, subjective examination uncovers that the (delicate )arrangements found by the model concur well with our instinct.
to learn more about neural machine translation
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