The hottest Dynamic Programming Substack posts right now

And their main takeaways
Category
Top Technology Topics

Problem 80: Unique Paths[Google]

Technology Made Simple • 39 implied HN points • 23 Mar 23
🕹 Technology Coding Dynamic Programming Recursion
  1. The problem discussed in the post is about finding unique paths in a grid using dynamic programming and recursion.
  2. The example solutions provided in the post illustrate how a robot can navigate from the top-left corner to the bottom-right corner in different grid sizes.
  3. The author also shares personal information about being a university student seeking work post-graduation and invites readers to check out their resume and LinkedIn profile.

[Solution]Problem 56:Climbing Stairs[Amazon]

Technology Made Simple • 79 implied HN points • 16 Sep 22
🕹 Technology Dynamic Programming Logic Recursion Math
  1. The post discusses a solution for the climbing stairs problem with dynamic programming, logic, recursion, and math.
  2. The problem involves finding the number of distinct ways to climb to the top of a staircase by either taking 1 or 2 steps at a time.
  3. The post provides examples and constraints for the problem, along with a link to test the solution on Leetcode.

Problem 56:Climbing Stairs[Amazon]

Technology Made Simple • 59 implied HN points • 15 Sep 22
🕹 Technology Dynamic Programming Logic Recursion Math
  1. The post discusses a problem related to climbing stairs, involving dynamic programming, logic, recursion, and math.
  2. The problem presents a scenario where you can climb a certain number of steps to reach the top, and you have to find the distinct ways to do so.
  3. Examples and constraints are given, along with a link to test your solution on Leetcode.

Problem 55:Playlist with Buffer[Apple]

Technology Made Simple • 39 implied HN points • 07 Sep 22
🕹 Technology Dynamic Programming Logic Combinatorics
  1. The post discusses a problem related to creating a suitable music playlist for a road trip, requiring a certain number of songs and buffer between repeats.
  2. It emphasizes the importance of dynamic programming, logic, and combinatorics in solving the mentioned playlist problem.
  3. The post also includes requests to engage with and share the newsletter, showcasing the value of community support and feedback.
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Recursive Leap of Faith [Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 18 May 22
🕹 Technology Programming Recursion Dynamic Programming Algorithms Software Development
  1. The 'Recursive Leap of Faith' technique is a powerful approach in recursion where we assume our recursive calls will work as expected, simplifying our problem-solving process.
  2. By using the Leap of Faith, we can break down recursive problems into base cases and recursive steps, making it easier to navigate through complex coding challenges.
  3. To master the Recursive Leap of Faith technique, consistent practice is key. Breaking down problems into base cases and making assumptions about recursive calls helps build proficiency over time.

Steps for building Recursive solutions[Technique Tuesday]

Technology Made Simple • 39 implied HN points • 13 Apr 22
🕹 Technology Coding Tutorial Algorithm Recursion Dynamic Programming
  1. Developing recursive solutions involves creating conjectures, working from base cases, and simplifying complex problems into already solved ones.
  2. Starting with a brute force solution is crucial before attempting dynamic programming for optimal solutions.
  3. Building a strong foundation in recursive thinking is key to mastering more complex concepts like dynamic programming.

[Solution]Problem 29: Arranging Coins in Staircase[Netflix]

Technology Made Simple • 19 implied HN points • 18 Mar 22
🕹 Technology Lists Math Dynamic Programming Recursion Coding
  1. The problem involves arranging coins in a staircase with specific row numbers, and the solution focuses on finding the maximum number of complete rows that can be built.
  2. The solution involves analyzing the input (number of coins) and output (number of complete rows), and working through a simple approach using math to determine the complete rows.
  3. To improve the solution further, simplifications can be made to optimize the algorithm, aiming for a faster runtime complexity close to square root of n.

Problem 29: Arranging Coins in Staircase[Netflix]

Technology Made Simple • 19 implied HN points • 16 Mar 22
🕹 Technology Math Lists Dynamic Programming Recursion
  1. Optimal solutions in coding interviews can impress interviewers and require O(1) time and space complexity.
  2. In a coding problem like this one involving arranging coins in a staircase, understanding the complete rows and incomplete rows is key to solving it.
  3. Preparation for coding interviews, like practicing on Leetcode, can help in tackling similar problems and improving problem-solving skills.

[Solution]Problem 23: Maximize coin collecting[Zillow]

Technology Made Simple • 19 implied HN points • 03 Feb 22
🕹 Technology Recursion Dynamic Programming
  1. Understand and identify the recursive nature of a problem before moving on to find solutions.
  2. Recognize and handle terminal cases effectively, such as stopping at the bottom-right corner and dealing with cells in the last row or column.
  3. Optimize solutions by applying techniques like memoization in dynamic programming to store and reuse calculated values.
  4. Tip: Lead an interviewer to show understanding even if it's a complex problem with an exponential runtime solution.

[Solution]Problem 17: Minimum cost of painting N houses up to K different colors.[Facebook]

Technology Made Simple • 0 implied HN points • 23 Dec 21
🕹 Technology Coding Algorithm Dynamic Programming Optimization Complexity
  1. The problem involves minimizing cost while ensuring no neighboring houses have the same color. This can be represented using a matrix.
  2. Brute force can be initially used to explore all combinations, but dynamic programming is a more efficient approach in this scenario. Dynamic programming optimizes calculations by avoiding unnecessary computations.
  3. By utilizing dynamic programming, we can efficiently calculate the minimum cost of painting the houses with different colors. This method involves maintaining a matrix cache to track the costs and ensure the color constraint is met.