Leon Noel

DS & Algorithms?

#100Devs

"Then when I asked, "Do ya have a man?", she tried to pretend
She said: "No, I don't, I only have a friend""

Agenda

  • Questions?

  • Discuss - #HUNTOBER2022

  • Discuss - You ARE ready!

  • Learn - Basic DS & Algorithms

  • Homework

Questions

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#HUNTOBER2022

Daily Question

Daily Standup

(Mon-Fri 6pm EST)

 

 

 

 

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Friday 6:00pm ET on Discord

SUNDAY SUPER REVIEW

1pm ET 

 

 

 

 

5 More Classes

 

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P.R.E.P

Parameters, Returns, Examples, Pseudo Code

Methods Questions

Brute Force

ITS ALL YOU NEED

"Just had a coffee chat was told they see so many applicants with empty githubs, no portfolio sites and no projects under their belt

 

We’re on the right track yall, Leon has definitely given us the cheat codes"

 

@Telescope_Thieves

There was no technical assessment, I just told them about the projects I had worked on and made sure I was friendly and connected with them as people. I know there's lots of people here that are better coders than me, so it's absolutely possible you can do this!
Don't stop believing, stay consistent, and it will happen!

 

Sean, SOFTWARE FUCKING ENGINEER!

Was going to cancel the interview, but friend convinced them last minute

 

Works part time, gets paid full time!

 

Erica

BUILT A BUTTON WITH HTML & CSS
NO CODING CHALLENGE

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Daddy_Anki

Data Structures &
Algorithms

 An algorithm is just the steps you take to solve a problem 

 An algorithm is just a function 

This function transforms a certain input aka data structure

Into a certain output aka another data structure

The function contains logic that decides the transformation of the input to output

Think of a library

Thanks Scotch.io

A library contains many data structures

  • Books

  • Magazines

  • CDs

  • DVDs

  • Blu-rays

If your data is a bunch of text, it makes sense to use a book to hold it.

If your data is a bunch of low quality video, it makes sense to use a dvd to hold it.

DVDs have a limit on the amount of data they can hold. Cheaper but constrained

Blu-rays can hold more data, but they cost more

When worrying about real data, it is also cost, but in space and time

Think of a linked vs. doubly linked list

Less Memory, but Less Efficient

More Memory, but More Efficient

To make good decisions as engineers we need to understand the different structures for our data

Back to the library

The best data structures consume minimal resources while storing data in a meaningful way for various operations

Flip Book vs. DVD

What if we want a specific book?

Data Structure

in equals string

Data Structure 

out equals book

AKA our:

ALGORITHM

Do you check every book? 

How much time does it take to move through each book?

Do you have to remember all the rows you already checked?

Question:
What would be the most efficient way to find the book?

How long it takes to find the book is our

Time Complexity

Thinking through the appropriate data structures and algorithms is how we can efficiently solve problems

When taking about the effecientness or complexity of a solution we can use

Big-O Notation

Big-O notation mathematically describes the complexity of an algorithm in terms of time and space

Common Complexities

Git Connected Big O Article

O(1)

For all inputs to our algorithm there is and will always be only one operation required

  • Order 1
  • Constant Time

O(1) Example

No matter how many inputs are located in num there will only ever be one operation needed!

const nums = [1,2,3,4,5] 
const firstNumber = nums[0]

O(N)

For all inputs to our algorithm there will be one

operation per input

  • Order n
  • Linear
  • Linear Scailing

O(N) Example

Here we sum the numbers in the array. We have to add each number to a running sum, so we have to operate on each one. This means one operation per input.

const nums = [1,2,3,4,5]
let sum = 0
for(let num of nums){
	sum += num
}

O(1) VS O(N)

Summing function for a sorted, contiguous array of integers that starts with the number 1? Could easily be O(n) but...

const sumContiguousArray = function(ary){ 
  //get the last item
  const lastItem = ary[ary.length - 1]
  //Gauss's trick
  return lastItem * (lastItem + 1) / 2
}
const nums = [1,2,3,4,5]
const sumOfArray = sumContiguousArray(nums)

Committing these to memory is important

O(N^2)

Order N Squared

Text

const hasDuplicates = function(num){ 
  for(let i = 0; i < nums.length; i++){
    const thisNum = nums[i]
    for(let j = 0; j < nums.length; j++){
      if(j !== i){ 
        const otherNum = nums[j]
        if(otherNum === thisNum) return true
       }
    }  
  }
  return false
}

const nums = [1,2,3,4,5,5]
hasDuplicates(nums) //true

O(N^2)

Here we’re iterating over our array, which we already know is O(n), and another iteration inside it, which is another O(n). For every item in our list, we have to loop our list again to calculate what we need.

Homework