Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People

I recently read Grokking Algorithms: An Illustrated Guide for Programmers and Other Curious People and it really inspired me to open-source my notes

Quick TLDR; on who I am: I’m a 15yo (at the time of writing this) self-driving car enigneer, one of the youngest in the world. Am super fascinated by self-driving and how we can create a generalized, end2end model, capable of having robust preformance fully through Computer Vision. Recently built DataGAN

Now: currently buidling a fully e2e mdoel through Computer Vision. Here’s my repo for code + current progress. Here’s a tweet showing self-driving in steering (take a look below!)

As featured in: Udacity [blog] [video] + David Silver’s blog!

Note

This project is under active development atm and I’m currently working on importing my notes ASAP.

Contents

One more thing to note: the digram/italic text will usually be from the textbook itself. I do not take any credit for the amazling illustrations provided!

• Binary search
  • The search problem
  • Code
• Running time
• Lists + Arrays
  • The problem with lists
  • Insertion
  • Deletion
  • Arrays vs lists?
• Selection sort
  • Music!
  • Code
• Recursion
  • The problem with recursion?
  • Code
  • The problems with call stack
• Divide and Conquer
• Quicksort
  • Running times
  • Code
• Hash tables
  • Running time
• Graphs + Breadth-first search
  • Linear programming
  • Queues
• Dijkstra’s Algorithm
  • In code
• Greedy algorithms
  • The set-covering problem
• Dynamic Programming
  • The knapsack problem
  • Longest common subsequence
  • Applications of dynamic programming
• k-Nearest Neighbors
• Binary trees
• Inverted indexes
• Fourier transform
• Parallel algorithms
  • MapReduce
• Bloom filters + HyperLogLog
• SHA algorithms
• Diffie-Hellman key exchange