深度學習數據自動編碼器

意見 (Opinion)

When I first wanted to learn programming, I coded along to a 4 hour long YouTube tutorial.

剛開始學習編程時，我編寫了長達4個小時的YouTube教程。

“Great,” I thought after finishing the course. “I know how to code now!”

“ 好極了 ，”完成課程后我想。 “ 我現在知道如何編碼！ ”

I was excited! I wanted to learn more.

我很興奮！ 我想了解更多。

So I took another tutorial.

因此，我參加了另一個教程。

Then….. I took another.

然后.....我又拿了一個。

And yet another.

還有一個。

Sound familiar?

聽起來有點熟？

This went on for some time, until I finally gave up on trying to learn how to code.

這持續了一段時間，直到我最終放棄嘗試學習編碼的方法。

I was so used to structured classes, and there seemed to be no well-defined syllabus that would take me from “zero to hero” in coding.

我已經習慣了結構化的類，似乎沒有一個明確的提綱可以使我從“零到英雄”編碼 。

“Well, at least I tried. Now I know this isn’t for me,” I thought to myself.

“ 好吧，至少我嘗試過。 現在我知道這不適合我 ，”我對自己想。

Fast forward a year later, after talking to a few programmers and doing some reading of my own, I realized I was stuck in something called a tutorial trap.

一年后的今天，在與一些程序員交談并閱讀了一些自己的文章之后，我意識到自己陷入了一個教程陷阱。

什么是教程陷阱？ (What Is The Tutorial Trap?)

The tutorial trap is really easy to fall into.

教程陷阱確實很容易陷入。

You want to learn to code. Someone out there promises to make you a programmer if you take their course.

您想學習編碼。 如果您上了這門課程，那么有人會許諾讓您成為一名程序員。

You take the course.

您參加課程。

You do this again and again, with new frameworks and languages.

您會使用新的框架和語言來一次又一次地執行此操作。

This is a very tricky situation to be in, especially since you actually feel like you’re learning something during each tutorial.

這是一個非常棘手的情況，尤其是因為您實際上覺得自己在每個教程中都在學習一些東西。

Unfortunately, you are unable to apply anything you have learnt. You can’t come up with your own piece of code to solve a problem, let alone create an entire project from scratch.

不幸的是，您無法應用所學到的任何東西。 您無法提出自己的代碼來解決問題，更不用說從頭開始創建整個項目了。

If this is you, then its time to break out of the tutorial trap.

如果是您，那么是時候擺脫教程陷阱了。

突破教學陷阱 (Breaking Out of The Tutorial Trap)

Laurentiu Iordache on Laurentiu Iordache攝于UnsplashUnsplash

If you’re reading this article because you want a well-defined syllabus to become a programmer, you’re in the wrong place.

如果您要閱讀明確的課程大綱是因為希望有一個定義明確的課程大綱成為程序員，那么您來錯了地方。

Everybody’s path towards learning to code is different. I will simply point you in the right direction based on what worked for me.

每個人學習編碼的途徑都不同。 我只會根據對我有用的內容，為您指明正確的方向。

To break out of the tutorial trap, you first need to stop taking tutorials.

要突破教程陷阱，您首先需要停止學習教程 。

If you have taken one or two online courses, you know the basic syntax and operators.

如果您參加了一到兩門在線課程，您將了解基本語法和運算符。

• Variables
  變數
• Functions
  功能
• Control Flow
  控制流
• Loops
  循環
• Arrays
  數組

Once you are familiar with the basics and how these work, move on!

一旦您熟悉了基礎知識以及它們如何工作，就繼續吧！

All online courses will teach you the same thing, and taking more than one is just going to waste your time.

所有的在線課程都會教給您同樣的事情，而花很多時間都只會浪費您的時間。

知道這一點后，繼續進行一些小的編碼挑戰。 (After you know this, move on and start doing some small coding challenges.)

Photo by Jukan Tateisi on Unsplash Jukan Tateisi在Unsplash上拍攝的照片

My personal favourite is a website called HackerRank. They have challenges with varying difficulty levels.

我個人最喜歡的是一個名為HackerRank的網站。 他們面臨的挑戰具有不同的難度級別。

This is a great way to get started with programming once you know the basics. It will help you familiarise yourself with the language.

一旦掌握了基礎知識，這就是開始編程的好方法。 它將幫助您熟悉該語言。

These challenges might be a little intimidating at first, since it is your first time solving a problem without coding along.

這些挑戰乍一看可能有些嚇人，因為這是您第一次無需編碼即可解決問題。

If you get stuck along the way, looking at another person’s code will also really help you start thinking. (Don’t just copy paste their code, try to understand how they solve it.)

如果您一路陷入困境，那么查看他人的代碼也將真正幫助您開始思考。 ( 不要只是復制粘貼他們的代碼，而是嘗試了解他們如何解決它。)

As you look at other people’s code, you will notice that they are all different. There is always more than one way to look at a problem, and so many different approaches you can take.

當您查看其他人的代碼時，您會發現他們都是不同的。 解決問題總是有不止一種方法，因此可以采取許多不同的方法。

This will really change the way you think as a programmer, and improve your ability to code.

這將真正改變您作為程序員的思維方式，并提高您的編碼能力。

專案，專案，專案 (Projects, Projects, Projects)

Photo by Jo Szczepanska on Unsplash Jo Szczepanska在Unsplash上拍攝的照片

Once you have developed some confidence in your ability to code without following a tutorial, you can start with projects!

一旦對無需進行教程的編碼能力有了一定的信心，就可以從項目開始！

開始之前請牢記最終產品 (Have an end-product in mind before you start)

When I first started out in the data analytics field, I read the same piece of advice everywhere.

當我第一次進入數據分析領域時，我到處都讀到同樣的建議。

Do projects!

做項目！

However, I had no idea what projects to do. Everytime I started something, it would go nowhere and I would never end up completing it.

但是，我不知道要做什么項目。 每當我開始做某事時，它就無濟于事，而且我永遠也不會最終完成它。

This is because I had no solid goal in mind.

這是因為我沒有堅定的目標。

When creating a project, always have one solid end goal in mind. Also, make sure it is a project you are interested in doing. Otherwise you’ll never end up completing it.

創建項目時，始終牢記一個堅實的最終目標。 另外，請確保這是您感興趣的項目。 否則，您將永遠無法完成它。

這是一個例子： (Here’s an example:)

You want to analyze trends in the music industry over time.

您想分析音樂行業隨著時間的趨勢。

End goal: Finding patterns in music trends over time, with data such as artist name and genre.

最終目標：利用藝術家姓名和流派之類的數據來查找音樂趨勢隨時間變化的模式。

In order to do this, you will first need to collect the data.

為此，您首先需要收集數據。

This can be done with the help of a web scraper or an API. This will require quite a lot of coding, and is a great intermediate level coding project by itself.

這可以借助網絡抓取器或API來完成 。 這將需要大量的編碼，并且本身就是一個很好的中級編碼項目。

Then, you will need to clean the data. This is a simple task, but can be very time consuming because of just how messy the data can be.

然后，您將需要清除數據。 這是一個簡單的任務，但由于數據可能非?；靵y，因此可能非常耗時。

You don’t need to have high level programming skills to perform data analytic tasks. Most of what needs to be done is data manipulation, which doesn’t require much logic to do.

您無需具備高級編程技能即可執行數據分析任務。 大部分需要做的是數據操作，不需要太多的邏輯即可完成。

Finally, you can perform the actual analysis. You will need to know how to use visualization libraries in order to do this, which are pretty easy to pick up on. Matplotlib and Seaborn are two popular Python visualization libraries.

最后，您可以執行實際分析。 您將需要知道如何使用可視化庫來執行此操作，這很容易上手。 Matplotlib和Seaborn是兩個流行的Python可視化庫。

而已！ (That’s it!)

This is just a rough idea on the steps you should take to learn coding for data science.

這只是關于學習數據科學編碼應采取的步驟的一個粗略想法。

I understand that data science is a field that attracts people from various different backgrounds. If you are from a non-technical background, the coding part may seem really intimidating at first.

我了解數據科學是一個吸引來自不同背景的人們的領域。 如果您來自非技術領域，那么編碼部分起初似乎確實令人生畏。

Everyone seems to be writing these really complex, large pieces of code that don’t make sense.

似乎每個人都在編寫這些毫無意義的大型代碼。

但是，您需要記住，每個人都從某個地方開始。 (However, you need to remember that everyone starts somewhere.)

Even the best programmer started out with “Hello World,” and you just need to be patient.

即使是最好的程序員，也都是從“ Hello World”開始的，您只需要耐心等待即可。

Give yourself some time to learn, and embrace the learning curve. Just like learning to swim, drive, or ride a bike, learning to code doesn’t happen overnight. It takes a lot of practice and staring at a computer screen to get there.

給自己一些時間來學習，并擁抱學習曲線。 就像學習游泳，開車或騎自行車一樣，學習編碼并不是一overnight而就的。 這需要大量的練習，并且盯著計算機屏幕才能到達那里。

I hope this article was helpful, thanks for reading!

希望本文對您有所幫助，感謝您的閱讀！

Making mistakes simply means you are learning faster — Weston H Agor

犯錯誤只是意味著您學習得更快— Weston H Agor

翻譯自: https://towardsdatascience.com/how-to-learn-coding-for-data-science-28df2705dac9

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