81 回覆

Are you sure?

數學唔係科學

1. 科學用cumulative evidence去驗證 (induction) 數學用logical deduction

2. 科學會做實驗 數學唔會

3. 科學永遠都係錯 但不斷接近真理

數學永遠都啱

4. 科學建基於現實世界

數學係純概念活動 而且係自明

1. 科學用cumulative evidence去驗證 (induction) 數學用logical deduction

2. 科學會做實驗 數學唔會

3. 科學永遠都係錯 但不斷接近真理

數學永遠都啱

4. 科學建基於現實世界

數學係純概念活動 而且係自明

如果計埋嗰啲social science, management science, investment science 科學有幾個特點

1. 要從現實揾evidence

2. 量化/optimisation

3. model現實

4. 做實驗 包括run simulation/data set

你哋咪睇吓cs中幾多

去到好theoretical嘅位應該會似數學多啲

1. 要從現實揾evidence

2. 量化/optimisation

3. model現實

4. 做實驗 包括run simulation/data set

你哋咪睇吓cs中幾多

去到好theoretical嘅位應該會似數學多啲

其實工程同科學唔係差好遠 只係一個出發點比較applied 另一個多啲純curiosity

反而數學同科學嘅分歧仲大

反而數學同科學嘅分歧仲大

你真係唔識架喎

返工返到懵咗

你真係乜柒都唔識架喎

引戰po

Computer engineering 先係engineering喎

shitty

現今Computer science讀嘅內容 已經唔係單單science 咁簡單，已經有engineering 嘅內容

Tell me when was the last time a CS theory was proven false or needed to be adjust because of it did not agree with experimental data.

That happens a lot in physics and other sciences. That's the way how science make progress but no CS. CS is mostly maths. You provre something is correct in CS because it is consistent with a set of axioms. We never run any experiment to verify axioms.

That happens a lot in physics and other sciences. That's the way how science make progress but no CS. CS is mostly maths. You provre something is correct in CS because it is consistent with a set of axioms. We never run any experiment to verify axioms.

係教細路教都懵咗。美國幼稚園已經有science。啲細路好細個已經要識乜係scientific method（上面果堆嘢）。

The crux is falsifiabiltiy.

https://en.wikipedia.org/wiki/Falsifiability

A scientific theory can be proven wrong by an experiment. It is a the best approximation of the reality we know until it is disproven. On the contrary CS/maths lacks this.

https://en.wikipedia.org/wiki/Falsifiability

A scientific theory can be proven wrong by an experiment. It is a the best approximation of the reality we know until it is disproven. On the contrary CS/maths lacks this.

Many Algorithms can prove false and need to be adjust because do not agree with experimental data.

Can you cite an example? I have read many algorithm research papers in the past. Typically there is a proof of correctness. It is like a proof in mathematics. You prove that the algorithm works based on some assumptions or axioms. i.e., you can derive the proof from a finite sequence of logical statements from the axioms. Then there it is usually accompanied by a time or space complexity analysis, which is also maths. If you can can prove that it is O(n * log n) time correctly, then there is no way to disprove it later.

If you propose an algorithm and claims that it 'works' based on limited experimental data, then yeah it works like science but this is not how algorithm research works.

If you propose an algorithm and claims that it 'works' based on limited experimental data, then yeah it works like science but this is not how algorithm research works.

呢幾年CS係偏Applied既

applied 都唔會係science，係engineering。

Let's throw this shit over the fence and see if it sticks. If not, change it a little and try again.

Let's throw this shit over the fence and see if it sticks. If not, change it a little and try again.

咁要睇你拉到幾寛

同埋science係咪就只能夠係傳統既natural science

同埋science係咪就只能夠係傳統既natural science

讀緊cs，我唔知

仲有forensic science