标签:tutorial
带有 tutorial 标签的公开 Whisper
划选高亮2026-08-11 12:23:48
原文高亮摘录
“the output of any sorting algorithm must satisfy two conditions”
Whisper 随想笔记
So that's why my custom sort broke — missed condition two.
划选高亮2026-08-11 03:09:57
原文高亮摘录
“List comprehensions provide a concise way to create lists.”
Whisper 随想笔记
List comprehensions are such a game changer, way cleaner than loops.
划选高亮2026-07-28 13:30:53
原文高亮摘录
“Recursive queries are typically used to deal with hierarchical or tree-structured data.”
Whisper 随想笔记
I've seen people do this with loops in app code, but SQL is way more elegant for it.
划选高亮2026-07-28 13:21:53
原文高亮摘录
“Recursive queries are typically used to deal with hierarchical or tree-structured data.”
Whisper 随想笔记
Yeah, I always reach for recursive CTEs when I need to walk a tree, it's the cleanest way.
划选高亮2026-07-28 13:01:34
原文高亮摘录
“Content-based filtering methods are based on a description of the item and a profile of the user's preferences”
Whisper 随想笔记
But what if the user's taste changes over time? This seems too static for that.
划选高亮2026-07-28 12:52:34
原文高亮摘录
“Content-based filtering methods are based on a description of the item and a profile of the user's preferences”
Whisper 随想笔记
So basically it just matches what you liked before with similar stuff, right?
划选高亮2026-07-28 10:20:53
原文高亮摘录
“A typical generative task is as follows. At each step, a datapoint is sampled from the dataset, and part of the data is removed, and the model must infer the removed part.”
Whisper 随想笔记
I've seen this in image inpainting too, not just text. Same trick, different domain.
划选高亮2026-07-28 10:03:18
原文高亮摘录
“Effects let you specify side effects that are caused by rendering itself, rather than by a particular event.”
Whisper 随想笔记
I remember debugging a chat app where I put the connection in an event—big mistake.
划选高亮2026-07-28 10:02:53
原文高亮摘录
“A typical generative task is as follows. At each step, a datapoint is sampled from the dataset, and part of the data is removed, and the model must infer the removed part.”
Whisper 随想笔记
So it's basically like playing a game of peek-a-boo with data, hiding a piece and making the model guess.
划选高亮2026-07-27 13:08:37
原文高亮摘录
“these functions return a null value when no rows are selected.”
Whisper 随想笔记
Yeah had to learn this the hard way, coalesce is a lifesaver.
划选高亮2026-07-27 13:06:13
原文高亮摘录
“Functions passed to event handlers must be passed, not called.”
Whisper 随想笔记
Makes sense, otherwise it runs immediately. I learned this the hard way too.
划选高亮2026-07-27 12:57:13
原文高亮摘录
“Functions passed to event handlers must be passed, not called.”
Whisper 随想笔记
Wait so I can't just do onClick={handleClick()}? That's been breaking my app for days, oops.
划选高亮2026-07-27 12:38:48
原文高亮摘录
“By strictly only writing your components as pure functions, you can avoid an entire class of baffling bugs”
Whisper 随想笔记
I've been burned by impure components before, this advice is gold.
划选高亮2026-07-27 10:17:52
原文高亮摘录
“You can do things by applying a method on a DataFrame or Series”
Whisper 随想笔记
Took me a while to get that methods change the data in place sometimes, confusing
划选高亮2026-07-27 09:59:52
原文高亮摘录
“You can do things by applying a method on a DataFrame or Series”
Whisper 随想笔记
Yeah but the real magic is when you chain like five methods together lol
划选高亮2026-07-27 09:56:37
原文高亮摘录
“Aggregate functions compute a single result from a set of input values.”
Whisper 随想笔记
Wish they'd show an example here, the docs are too dry for me.
划选高亮2026-07-27 09:28:15
原文高亮摘录
“A module is a file containing Python definitions and statements.”
Whisper 随想笔记
Wait, so if I just write some functions in a file, I can import them anywhere? Cool.
划选高亮2026-07-26 16:25:15
原文高亮摘录
“Even though the slice header is passed by value”
Whisper 随想笔记
This is exactly why slices feel like references even though they're not.
划选高亮2026-07-26 13:02:42
原文高亮摘录
“efficient application of the chain rule to neural networks”
Whisper 随想笔记
So many tutorials skip the 'efficient' part and just drown you in math.
划选高亮2026-07-26 10:05:24
原文高亮摘录
“an algorithm for first-order gradient-based optimization of stochastic objective functions”
Whisper 随想笔记
Finally an optimizer that just works without babysitting the learning rate.