BC MACHINE LEARNING
Saved by @CodyyyGardner

🤔 Python generators

What are they? How to use them?

#Python

🧵Let's find out 👇

 1️⃣ Python generators are lazy iterators delivering the next value when their .next() is called.

They are created by using the yield keyword

next() can be called explicitly or implicitly inside for loop

They can be finite or infinite
2️⃣ yield - where a value is sent back to the caller, but the function doesn’t exit afterward as with the return statement

The state of function is remembered.

For example, the number is incremented and sent back from yield at the consecutive call next()
3️⃣ Generator stores only the current state of the function - it generates next element on next() call and forgets the previous one -> it saves memory

For example, we don't need to store 1mio elements in memory to do something with each element
4️⃣ When you call a generator function generator object is returned - it's not executed yet

It executes only when next() is called

For example, that's why Exception is raised only on the next() call
5️⃣ When the generator goes out of elements it raises StopIteration exception
6️⃣ You can also create a class that behaves like a generator - it needs implemented methods:

- __iter__ -> to enable iteration
- __next__ -> to enable next element access
7️⃣ You can also create a generator with one-liner expression similar to list comprehension
8️⃣ You can read more:

https://t.co/mXp7L8l2Ai

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🧵👇


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There are several skills needed for learning machine learning that no one talks about.

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🧵👇

This thread aims to introduce to you some of the skills often ignored for learning machine learning but are actually very important.

These skills will enable you to learn concepts quickly and more efficiently in this field.

(2 / 9)

1⃣ Reading

Probably one of the most underrated skills on this list.

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Which libraries do you really need to get started with Machine Learning and why?

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(2 / 19)

If you know these topics, then you are good to go with machine learning in Python

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