DATA STRUCTURES you MUST know (as a Software Developer) | ความรู้การเรียนรู้ทั่วไปล่าสุด –

คุณกำลังพยายามหาข้อมูลเกี่ยวกับหัวข้อการหาเงินออนไลน์หรือไม่? คุณกำลังมองหาหัวข้อที่เหมาะสม DATA STRUCTURES you MUST know (as a Software Developer) หรือไม่? ถ้าเป็นเช่นนั้นโปรดอ่านบทความนี้ทันที.


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รูปภาพที่เกี่ยวข้องกับหัวข้อ data structures.

DATA STRUCTURES you MUST know (as a Software Developer)
DATA STRUCTURES you MUST know (as a Software Developer)

คุณสามารถค้นหาความรู้ที่เป็นประโยชน์เพิ่มเติมจากเราได้ที่นี่: ดูบทความที่นี่.

ควรอ่านเนื้อหาที่เกี่ยวข้องกับหัวข้อdata structures.

ภาพรวมที่ฉันอยากได้ตอนเริ่มต้น! 👨‍💻 เข้าร่วม Freemote ซึ่งเป็น Bootcamp นักพัฒนาอิสระ 🍿 เรียนรู้กลยุทธ์ “Zero to Freelance Developer” (ฟรี) 📸 Social media #datastructures #algorithms #basics.

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การค้นหาที่เกี่ยวข้องกับหัวข้อDATA STRUCTURES you MUST know (as a Software Developer).

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35 thoughts on “DATA STRUCTURES you MUST know (as a Software Developer) | ความรู้การเรียนรู้ทั่วไปล่าสุด –”

  1. One video, and I'm subbed. I appreciate the high-level explanation of these DS's, as I am a student. Also, I dig the subtleties and nuance of your design/imagery in your videos. Strong work, please keep it going!

  2. Without data structures, you can't solve algorithms, and without algorithms, you can't pass a programming interview, and without passing a programming interview, you can't spend all day doing CSS.

  3. The tail of the list is traditionally referring to "the rest of the list" – NOT the last element only. A traditional linked list has no last element, by definition. It's the head and the rest of the list, ie the tail. If you want to get the last element, you remove the head of the list, getting the tail. Which is the rest of the list. Now you have a new head. And a new tail. Keep removing the head until the rest of the list, the tail, is empty…. and you're at the last element of the list. This is why getting the last element of a linked list is O(n), which means that you have to go through all n elements to get the last one.

    Unless you implement double linked lists. Which is a list that have the same properties as the ordinary ones – but from both directions. In other words, neat to have if you need to have the last element often. Thing is, simplifying things is great for understanding but simplifying too much and it might be misleading or even wrong.

    What I wish they'd tell me when I was starting is more like: oh, the Big-O-notation is good to know and we're gonna teach you why – but in most cases in real life you won't care much about it. Choose whatever data structure you are comfortable with that solves your problem at hand. Once you're a software architect or builds stuff from scratch, you'll know what's important and not.
    What I really have appreciated and would love to put focus on is how to write maintainable code.

    I dare to say that the most unnescessary money spent in software projects is NOT optimizing slow programs. It's tryintg to get new team members to understand and master the code base for the solution – becoming efficient in maintaining the code. And extending it with new features.

  4. A question: Interviews are to determine if a person has ability to solve problems. Then they give these popular questions which a person can spend enough time to understand and memorize(if not only memorize in some cases)…isn't it obvious that the candidate must have learned how to solve this particular type of problem?…How is this a good criteria

  5. Great video I subscribed I'm learning Python and building my own clever but small program… turns out it's a graph data structure but I did not even know that until now

  6. Great explanations body. I came here from the trees one, will watch it 5 times more i guess jajaj. Regarding the big O notation, isn't for verifying the "worst" case based on the data and process structure. Memory and cpu, cycles or space and time. Like how bad could this go if the input varies this much. Please check me if i got it wrong ?

  7. This is a tutorial which I have to watch at a slower speed, 0.75. It's hard to process this much information under 8 minutes.
    But it's better than watching hours of tutorial without understanding anything


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