Приклади вживання So we put Англійська мовою та їх переклад на Українською
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Computer
So we put away a little food.
They were still alive, so we put them back in the water.
So we put a curb on it.
The season of apricots began, so we put them on the health benefits.
So we put the third row.
But, pilots are optimists- they have to be- so we put the kit in the helicopter.
So we put them to the test.”.
All of the x's from negative infinity to negative 1,but not including negative 1, so we put a parenthesis right there.
So we put ourselves in this position.".
So we put together a plan….
In this case, we're inputting two"x" plus three into our function, so we put two"x" plus three where the"x" is right over there.
So, we put two blanks together.
Every day we think about giving the best to our children, so we put all our effort so that they are well nourished;
So we put the patient on the MR table.
Treba's next as USB- s motherboard are not functional so we put a pleasant usb separate sites is not integrated on the motherboard….
So we put the last 500 in the crown.
It was alive so we put it back into the tide.
So we put those experiences on the page.
So we put that out on the wire: 1,400 tutors.
So we put people's needs in first place.
So we put the idea on the back burner for a few months.
So we put a lot of effort to train our specialists.
So, we put knee-pads, safety belts and helmets on them….
So we put off until tomorrow doing what we should have started yesterday, or the day before.
So we put our button on the product card, it's already working, and if you change the line in the code:.
So we put in the first place that we want to emphasize(just yesterday, not today, and I, not you, come and did not come, home, and not to visit).
And So We Put Goldfish in the PoolMakoto NagahisaJapan/ 2017, 28 min One summer day, 400 goldfish were found in the swimming pool of a secondary school.
So we put the patient on the MR table.We attach a transducer, in this case, to the brain, but if it will be a different organ, it will be a different transducer attached to the patient.
So we put his writings, letters, his interviews, correspondences, into a huge database of thousands of pages, and then used some natural language processing to allow you to actually have a conversation with him.