Answer:
Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. Greedy algorithms are used for optimization problems. An optimization problem can be solved using Greedy if the problem has the following property: At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem.
If a Greedy Algorithm can solve a problem, then it generally becomes the best method to solve that problem as the Greedy algorithms are in general more efficient than other techniques like Dynamic Programming. But Greedy algorithms cannot always be applied. For example, the Fractional Knapsack problem (See this) can be solved using Greedy, but 0-1 Knapsack cannot be solved using Greedy.
The following are some standard algorithms that are Greedy algorithms.
1) Kruskal’s Minimum Spanning Tree (MST): In Kruskal’s algorithm, we create an MST by picking edges one by one. The Greedy Choice is to pick the smallest weight edge that doesn’t cause a cycle in the MST constructed so far.
2) Prim’s Minimum Spanning Tree: In Prim’s algorithm also, we create an MST by picking edges one by one. We maintain two sets: a set of the vertices already included in MST and the set of the vertices not yet included. The Greedy Choice is to pick the smallest weight edge that connects the two sets.
3) Dijkstra’s Shortest Path: Dijkstra’s algorithm is very similar to Prim’s algorithm. The shortest-path tree is built up, edge by edge. We maintain two sets: a set of the vertices already included in the tree and the set of the vertices not yet included. The Greedy Choice is to pick the edge that connects the two sets and is on the smallest weight path from source to the set that contains not yet included vertices.
4) Huffman Coding: Huffman Coding is a loss-less compression technique. It assigns variable-length bit codes to different characters. The Greedy Choice is to assign the least bit length code to the most frequent character. The greedy algorithms are sometimes also used to get an approximation for Hard optimization problems. For example, the Traveling Salesman Problem is an NP-Hard problem. A Greedy choice for this problem is to pick the nearest unvisited city from the current city at every step. These solutions don’t always produce the best optimal solution but can be used to get an approximately optimal solution.
Answer:
Check below for the answer and explanations
Explanation:
Digital media coordinators are professionals that create and manage digital contents. They create and manage websites, blogs, social media platforms, e-commerce sites, etc.
To be a practitioner in this field, Claire needs a first degree in any of digital media, social sciences, communications, computer science and similar courses.
She needs to have a good knowledge of computer software, a high reasoning skill and a laudable communications skill.
Answer:
f = open('students.txt', 'r')
Explanation:
In the computing world, a command is an instruction to a computer program to execute a particular task. These instructions might be issued via a command-line interface, such as a shell program, or as a input to a network service as a component of a network protocol, or can be instructed as an event in a graphical user interface activated by the respective user selecting an option in a menu.
the f = open('students.txt', 'r') command line would be used to open a file named "students.txt", There are also various other types of commands for executing different task, for example:
1. ASSOC for Fix File Associations
2. FC for File Compare
3. IPCONFIG for IP Configuration
4. NETSTAT for Network Statistics
5. PING for Send Test Packets
6. TRACERT for Trace Route
7. POWERCFG for Power Configuration
e.t.c.
Can you please provide us with a photo of your personal fact sheet?
I believe it is commonly referred as a college/vocational school/ or a university.
