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Overlapping Subproblems Property: Tabulation | Intro to Dynamic Programming
Dynamic Programming
course content

Course Content

Dynamic Programming

Dynamic Programming

1. Intro to Dynamic Programming
2. Problems
3. Solutions

bookOverlapping Subproblems Property: Tabulation

Tabulation

"First, solve all necessary subproblems, and then solve the main problem."

Such a principle is called the Bottom-Up approach. We start with trivial subproblems and move from the bottom to the answer. This principle also uses additional tables to store solutions.

Example

Let’s create an array dp to store the solutions. (dp can be a common name for data structure in a class of DP problems).

1234567891011121314
def fib(n): # Array declaration dp = [0]*(n+1) # Base case assignment dp[0] = 0 dp[1] = 1 # Calculating and storing the values for trivial cases for i in range(2 , n+1): dp[i] = dp[i-1] + dp[i-2] return dp[n]
copy

Since we know how to calculate the next element using the previous two elements, let's move from the pre-defined first two elements (base case) and figure out the solution for the 3rd sub-problem. After that, solve the 4th sub-problem using the 2nd and 3rd, and so on, until the last element.

Task

Look at the following task code for the Fibonacci problem.

  1. Fix it to make the solution correct.
  2. Call the function for n = 16 and output the 16th Fibonacci number.

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Section 1. Chapter 3
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bookOverlapping Subproblems Property: Tabulation

Tabulation

"First, solve all necessary subproblems, and then solve the main problem."

Such a principle is called the Bottom-Up approach. We start with trivial subproblems and move from the bottom to the answer. This principle also uses additional tables to store solutions.

Example

Let’s create an array dp to store the solutions. (dp can be a common name for data structure in a class of DP problems).

1234567891011121314
def fib(n): # Array declaration dp = [0]*(n+1) # Base case assignment dp[0] = 0 dp[1] = 1 # Calculating and storing the values for trivial cases for i in range(2 , n+1): dp[i] = dp[i-1] + dp[i-2] return dp[n]
copy

Since we know how to calculate the next element using the previous two elements, let's move from the pre-defined first two elements (base case) and figure out the solution for the 3rd sub-problem. After that, solve the 4th sub-problem using the 2nd and 3rd, and so on, until the last element.

Task

Look at the following task code for the Fibonacci problem.

  1. Fix it to make the solution correct.
  2. Call the function for n = 16 and output the 16th Fibonacci number.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Section 1. Chapter 3
toggle bottom row

bookOverlapping Subproblems Property: Tabulation

Tabulation

"First, solve all necessary subproblems, and then solve the main problem."

Such a principle is called the Bottom-Up approach. We start with trivial subproblems and move from the bottom to the answer. This principle also uses additional tables to store solutions.

Example

Let’s create an array dp to store the solutions. (dp can be a common name for data structure in a class of DP problems).

1234567891011121314
def fib(n): # Array declaration dp = [0]*(n+1) # Base case assignment dp[0] = 0 dp[1] = 1 # Calculating and storing the values for trivial cases for i in range(2 , n+1): dp[i] = dp[i-1] + dp[i-2] return dp[n]
copy

Since we know how to calculate the next element using the previous two elements, let's move from the pre-defined first two elements (base case) and figure out the solution for the 3rd sub-problem. After that, solve the 4th sub-problem using the 2nd and 3rd, and so on, until the last element.

Task

Look at the following task code for the Fibonacci problem.

  1. Fix it to make the solution correct.
  2. Call the function for n = 16 and output the 16th Fibonacci number.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Everything was clear?

How can we improve it?

Thanks for your feedback!

Tabulation

"First, solve all necessary subproblems, and then solve the main problem."

Such a principle is called the Bottom-Up approach. We start with trivial subproblems and move from the bottom to the answer. This principle also uses additional tables to store solutions.

Example

Let’s create an array dp to store the solutions. (dp can be a common name for data structure in a class of DP problems).

1234567891011121314
def fib(n): # Array declaration dp = [0]*(n+1) # Base case assignment dp[0] = 0 dp[1] = 1 # Calculating and storing the values for trivial cases for i in range(2 , n+1): dp[i] = dp[i-1] + dp[i-2] return dp[n]
copy

Since we know how to calculate the next element using the previous two elements, let's move from the pre-defined first two elements (base case) and figure out the solution for the 3rd sub-problem. After that, solve the 4th sub-problem using the 2nd and 3rd, and so on, until the last element.

Task

Look at the following task code for the Fibonacci problem.

  1. Fix it to make the solution correct.
  2. Call the function for n = 16 and output the 16th Fibonacci number.

Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
Section 1. Chapter 3
Switch to desktopSwitch to desktop for real-world practiceContinue from where you are using one of the options below
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