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Back To Back SWE
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Добавлен 6 янв 2017
This channel is our initiative to add to the community of programming interview preparation. It took us a long time to realize while preparing for the first software engineering interview we felt that the resources on programming interviews are not only sparse, but there lacked an abundance of people who could explain answers to interview questions in a way that a student could easily understand.
This channel aims to prepare someone to pass software engineering interviews at "the big 4" companies and any other large tech companies.
Grow with Us and Let's Ace those Interviews 🚀
This channel aims to prepare someone to pass software engineering interviews at "the big 4" companies and any other large tech companies.
Grow with Us and Let's Ace those Interviews 🚀
Build A Min Height BST From A Sorted Array | Coding Interview Question
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Given a sorted array, create a binary search tree with minimal height.
Input:
[1, 2, 3, 4, 5, 6, 7]
Output:
[4, 2, 6, 1, 3, 5, 7]
Explanation:
4
/ \
2 6
/ \ / \
1 3 5 7
Free 5-Day Mini-Course: backtobackswe.com
Try Our Full Platform: backtobackswe.com/checkout?plan=lifetime-legacy&discount_code=APRIL40
📹 Intuitive Video Explanations
🏃 Run Code As You Learn
💾 Save Progress
❓ New Unseen Questions
Given a sorted array, create a binary search tree with minimal height.
Input:
[1, 2, 3, 4, 5, 6, 7]
Output:
[4, 2, 6, 1, 3, 5, 7]
Explanation:
4
/ \
2 6
/ \ / \
1 3 5 7
Просмотров: 7 026
Видео
AVL Trees & Rotations (Self-Balancing Binary Search Trees)
Просмотров 329 тыс.4 года назад
AVL Trees & Rotations (Self-Balancing Binary Search Trees)
The New Back To Back SWE Platform (2020 Plans)
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The New Back To Back SWE Platform (2020 Plans)
Network Flows: Max-Flow Min-Cut Theorem (& Ford-Fulkerson Algorithm)
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Network Flows: Max-Flow Min-Cut Theorem (& Ford-Fulkerson Algorithm)
Interval Scheduling Maximization (Proof w/ Exchange Argument)
Просмотров 61 тыс.4 года назад
Interval Scheduling Maximization (Proof w/ Exchange Argument)
Dijkstra's Algorithm vs Prim's Algorithm
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Dijkstra's Algorithm vs Prim's Algorithm
Professor Clyde Kruskal On Kruskal's Algorithm
Просмотров 40 тыс.4 года назад
Professor Clyde Kruskal On Kruskal's Algorithm
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Why Comparison Based Sorting Algorithms Are Ω(n*lg(n))
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Why Comparison Based Sorting Algorithms Are Ω(n*lg(n))
Software Engineer On Negotiating Job Offers & Finding The Right Workplace (Samrat Jha - B2B Show 3)
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Software Engineer On Negotiating Job Offers & Finding The Right Workplace (Samrat Jha - B2B Show 3)
Serialize & Deserialize A Binary Tree - Crafting Recursive Solutions To Interview Problems
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Serialize & Deserialize A Binary Tree - Crafting Recursive Solutions To Interview Problems
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Find the k'th Largest or Smallest Element of an Array: From Sorting To Heaps To Partitioning
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Counting Sort: An Exploration of Sorting Special Input In Linear Time
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Sort A K Sorted Array - Investigating Applications of Min/Max Heaps
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Sort A K Sorted Array - Investigating Applications of Min/Max Heaps
Lowest Common Ancestor Between 2 Binary Tree Nodes (A Recursive Approach)
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Lowest Common Ancestor Between 2 Binary Tree Nodes (A Recursive Approach)
The Quicksort Sorting Algorithm: Pick A Pivot, Partition, & Recurse
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The Quicksort Sorting Algorithm: Pick A Pivot, Partition, & Recurse
Search A 2D Sorted Matrix - Fundamentals of Search Space Reduction
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Search A 2D Sorted Matrix - Fundamentals of Search Space Reduction
Fast Multiplication: From Grade-School Multiplication To Karatsuba's Algorithm
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The Backtracking Blueprint: The Legendary 3 Keys To Backtracking Algorithms
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Investigating Heap Sort - Why Is Heap Sort Θ(n * log(n))? An Even Longer Really Long Answer.
Просмотров 64 тыс.5 лет назад
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Reverse Polish Notation: Types of Mathematical Notations & Using A Stack To Solve RPN Expressions
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Reverse Polish Notation: Types of Mathematical Notations & Using A Stack To Solve RPN Expressions
Add Two Numbers Without The "+" Sign (Bit Shifting Basics)
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Add Two Numbers Without The " " Sign (Bit Shifting Basics)
Minimum Window Substring: Utilizing Two Pointers & Tracking Character Mappings With A Hashtable
Просмотров 121 тыс.5 лет назад
Minimum Window Substring: Utilizing Two Pointers & Tracking Character Mappings With A Hashtable
Why Is Merge Sort O(n * log(n))? The Really Really Long Answer.
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Why Is Merge Sort O(n * log(n))? The Really Really Long Answer.
Egg Dropping Problem: Dynamic Programming Fundamentals & Understanding Subproblem Decomposition
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Longest Common Subsequence (2 Strings) - Dynamic Programming & Competing Subproblems
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Longest Common Subsequence (2 Strings) - Dynamic Programming & Competing Subproblems
You are very dedicated. Really cool!! Thanx
best kmp video on ytb
This exaplanation is awesome, wonderful. Thank for the wonderful service!!
Goat 🥂
Genius ❤
Amazing explanation on dynamic programming! For this example it would be a really cool to add transposition which adds a nice extra special case.
what an amazing way to build intuition for such problems! thank you!!
thanks it was good i never learnt it before like this it is nice but needs math that why IT always better to have good math grasp
Incredible video.
Thank you man
Great video!
amazing. thanks
Don't like to throw the race card in there but THANK YOU!
Amazing!!!
Within a minute or so, I knew this was going to be one of the best explanations I have seen or read. Thanks!
I've been reading Grokking Algorithms 2nd Edition, and found your explanation better. Though, I love the book too." One thing that bothers me in most explanations, including in GA2ndEd, is that they rarely deal with the case where the item you are looking for is the last one. In your example, of 1, 2, 3, 4, 5, 6, 7, 8 if we are looking for "8", and using the floor division approach (which GA2ndEd uses) we start with index 3, too low. Next we look at "5" within 5, 6, 7, 8. 2nd attempt, too low. Next we look at 7 within 7,8. Third attempt, and still too low. Now, unless we know ahead of time that the item we're looking for is guaranteed to be in the set, then we must make a 4th comparison to verify that 8 is indeed the last available item to examine. The book says it is going to explain this in chapter 4 (I'm only on 3) as to why constants are not used in Big O notation, but I just wish they and others would note this nuance when the list of items is a power of 2.
row = int(input()) user_input = [] for i in range(row): user_input.append(list(map(int, input().split()))) def kadane(user_input): max_global = float("-inf") max_current = 0 for i in range(len(user_input)): max_current += user_input[i] if max_current > max_global: max_global = max_current if max_current < 0: max_current = 0 return max_global max_global = float("-inf") running_row_sum = [0] * len(user_input) for run in range(len(user_input[0])): running_row_sum = [0] * len(user_input) for l in range(run, len(user_input[0])): for r in range(len(user_input)): current_number = user_input[r][l] running_row_sum[r] += current_number best_max_sub_list = kadane(running_row_sum) if best_max_sub_list > max_global: max_global = best_max_sub_list print(max_global) acm.timus.ru/problem.aspx?space=1&num=1146
Great video
Very Helpful, Fantastic Explanation
Love this video
ive left more confused than before. :(
8:02, why do we move backwards in the array arr? Is there any reason behind this? Why not moving forwards?
THANK YOU SO MUCH!!!!!
Nice video man. I like your style of teaching, this is the first ever video of yours that I've watched and I like the casual style of teaching. It would be great if you could make videos that emphasize the guiding principle behind solving a problem and then share ways to attack the problem as well, in a direct way. Thanks and Cheers!
8:14 starts here
Absolutely the best video to explain this. Just took away all my frustration lol!!
Greate video, Thanks a lot!
i think you're the love of my life
Thank you!!!
Hath Mila Bhai 🤝
why are you explaining things better than the people who get paid to do it? why do I have to pay 1800 for college credit to learn the material on youtube?
Amazing wonderfully explained
super super love this
Well done
Thank you so much!
1. why we are ONLY able to put the new left/right Parentheses at the rightest side every time? 2. According to the above limitation, why we could say the final level leafs are the answer? Thanks 🙇♂
Nice explanation :)
16:25 he makes this feel so epic.
lol got this question for amazon applied scientist role 2 years ago and i didn't know it was LRU cache
I've struggled with the knapsack problem for so long. I learned a lot from your video. Thank you!
Great Explanation
TY so much great explanation and I dont even speak english that well! Love from italy
Thank you so much
at 6:00 I was like, say no more => Subscribed. fkn love the way explain stuff man
good job brother very appreciate it
Best expiation ever sir. Thank you so much for your efforts.
Thank you, sir! You explained it with great energy and clarity.
Sorry but show big trees not that small stuff
nice, thank you
Is it possible to solve this question without looking at solution ?
Very detailed explanation with a big array! Thank you .