| Tue | Wed | Thu | Fri | Sat | Sun | Mon | |:-:|:-:|:-:|:-:|:-:|:-:|:-:| | [May 23](05-23-2023) | [May 24](05-24-2023.md) | [May 25](05-25-2023.md) | **Today** | [May 27](05-27-2023.md) | [May 28](05-28-2023.md) | [May 29](05-29-2023) | # Friday, May 26, 2023 ## Notes - Installed Visual Studio Code without [[Microsoft]] - Added [[DeepFace]] Video:  - Looking for ways to improve/streamline data processing. Sharing a vault between Obsidian and VSC with plans to use VSC for code - web crawlers, formatting, etc. - Downloaded a LinkedIn scraper. <https://github.com/joeyism/linkedin_scraper> Browserflow Chrome Extension [Tutorials](https://browserflow.app/tutorials) - [Gallery](https://browserflow.app/gallery) Glasp Web Highlighter [Tutorial](https://medium.com/glasp/tutorial-how-to-export-web-articles-highlighted-sentences-into-obsidian-25d63285bcb9) From two weeks ago:  10 Key Data Structures We Use Every Day  ![[Types of Data Models - BDE.png]] - Lists are also useful in social media applications  like Twitter, where they can store and display   a user's feed in real-time, ensuring the  latest content is shown in the correct order. Arrays are another fundamental data structure. They provide a fixed-size,  ordered collection of elements. They are particularly well-suited for situations   where the size of the collection is  known or doesn't change frequently. - Stacks follow the Last-In-First-Out (LIFO) principle. They are perfect for supporting  undo/redo operations in text editors or maintaining browsing history in web browsers. - Trees organize data hierarchically. They are useful for representing data with natural hierarchies or relationships. They can be used in various applications, like database indexing, AI decision-making, and files systems. ![[Pasted image 20230526190115.png]] ![[Pasted image 20230526190138.png]] ![[Pasted image 20230526190237.png]] ![[Pasted image 20230526190255.png]] ![[Pasted image 20230526190413.png]] ![[Pasted image 20230526190434.png]] DATA STRUCTURES you MUST know (as a Software Developer)  > I wanted to explain the five most important data structures in this video in the way I understand them which means as little technical jargon as possible and just try to simplify it for you guys just starting out let's go first off let's talk about what a data structure is considering having a single data item like the price of a stock now that price on its own is not going to mean much but if we put it together with a bunch of stock prices let's say the price is over an entire day well then it becomes more meaningful we call date items that we grouped together like this compound data we have to store this data in some kind of data structure and choosing the right one is really important no data structure is perfect all them are good and bad at different things the way we measure how good a data structure is doing a specific thing like adding a new item retrieving an item sorting or searching is called the Big O notation this is pretty much a measure of how well in operation scales so if you have ten items, and then you add a million more how much longer will each operation take okay let's talk about the first data structure which is: - The Linked List (*atomic unit*) - "Node" - value and pointer - head → tail - Pros: good for adding and deleting items, because you just change where the next pointer is pointing. - Cons: Not great with searching, because each node is only aware of the one next to it. - Array - A continuous block of cells. - Good for retrieving items, because you know where it will be. - Hash Table - "it's an object in JavaScript or a dictionary in Python." - Con: Key collisions - Stack: Last in, first out. Push → Pop - Depth first search. - Queue: FIFO - Graphs and Trees - Pointers are called edges and can have weights. - Red/Black Trees Comment: *Take it from someone who learned how to code without the help of anyone: Coding is not too different than things you already know, it's just a language used to express your understanding of how to solve a problem, the first step is to "imagine" the steps of solving the problem in your head, you can do that using "common sense" and step by step procedures of breaking down a complex parts into smaller ones, after that what is left is learning what keys to press on your keyboard to "translate" the solution into computer language. you will NEVER be able to code something that you didn't solved in your head firsthand.* %% Footer Below%% ----  ------ # Keep Digging %%Space%% ## Explore Dates > - **Previous Day** - [[05-25-2023 ]] > - **Next Day** - [[05-27-2023 ]] > - **Day** - [[May 26th ]] > - **Month** - [[May 2023 ]] > - **Year** - [[2023 ]] > - **Decade** - [2020s](2020s.md) > - **Century** - [21st Century](21st%20Century) ## Tags #TL #TL/21st-Century #TL/2020-2029 #TL/2023 #TL/May/2023 #TL/May/26th ### Footnotes & References