These are my answers to the questions from LeetCode $90 course.

I am broke at the moment so can’t afford the $90 course.

• Arrays and strings
• Hashmaps and sets
• Linked lists
• Stacks and queues
• Trees and graphs
• Heaps
• Greedy algorithms
• Binary search
• Backtracking
• Dynamic programming

1. Arrays and Strings – Iterating over an array goes to show that each individual data point is being read in a linear time complexity. Strings form the basic building blocks of variables and constants. However in higher level order list format in cases of databases.
2. Hashmaps and Sets – Hashmaps are an intermediate form of algorithmic data structure. They are a combination of specific factors constants. They provide a combination data structure to combine to form new connections to point to final variables. // (May not be true) Sets are an advanced data structure, they use relation data graphs that use iteration sequencing to loop around data sets in order to get the wanted outcome output.
3. Linked Lists are an advanced form of algorithm data structure. They form connections between lists and enabling the formation of new arrays to find new solution variables. (Master object call and variable++, thereby overcoming Moore’s law)
4. Stacks are an intermediate form of data structure whereby several variable factors go through recursion to get a mean reversion variation order. Queues are set up algorithmic variables used mainly in Operating Systems (OS), they loop like in Python i++ but integrating with a external array factor in order to form a new queue data.
5. Trees are a simple, intermediate algorithmic data structure. They form the basis of neural networks that mirror real neural networks intelligences. They are a combination of hashmaps and queues. By using the hashmap algorithm function of putting together specific factor constants into lists (array-like). And using queue functionality (in coding) to get final factor variables. // Graphs are for artificial intelligence image generation and to a higher degree, ‘artificially’ enabling rotoscoping movements on a fixed data set of image datas.
6. Heaps when compared to Trees, of which trees have fixed constants, are interchangeable (manipulatable) data variables and objects, which are kind of like functions but are definitely not functions. They are in themselves, a unique form of data algorithm.
7. Greedy Algorithms are bloated RAM intensive algorithms
8. Binary Search is not a tree
9. Backtracking like in Google Backrub algorithm
10. Dynamic Programming are like for stacked queue lists (like Facebook Newsfeed)