Answer:
The answer is "Recovery Plan for Disasters".
Explanation:
In the given statement, some of the information is missing, which can be described as follows:
A) systems engineering plan
B) security compliance plan
C) risk assessment plan
D) Recovery Plan for Disasters
It is a set of guidelines for the execution of a recovery process, it provides the restoration and safety to the system for the organization in the event of a disaster. It defined as "a detailed summary of the appropriate acts to be carried out before, during and after a disaster", and incorrect choices were explained as follows:
- In option A, It is used to design and analyze complex systems.
- In option B, It provides frameworks for the corporate evaluation process.
- In option C, It is used to identify the problems.
Answer:
Computer professionals known as software engineers, or programmers use the software development life cycle to create software required for information systems.
Explanation:
Computer professionals are called software engineers and programmers because they develop and program software. Some additional titles for computer professionals are hardware engineers and iOS/Android developers.
Hello <span>Madysonhenders2477 </span><span>
Answer: Your mothers date of birth and a unique personal identification number (pin) code provide authentication by What you are (C)
Since your identification is about who you are, this would be the answer.
Hope This Helps!
-Chris</span>
Answer:
4. Supervised learning.
Explanation:
Supervised and Unsupervised learning are both learning approaches in machine learning. In other words, they are sub-branches in machine learning.
In supervised learning, an algorithm(a function) is used to map input(s) to output(s). The aim of supervised learning is to predict output variables for given input data using a mapping function. When an input is given, predictions can be made to get the output.
Unsupervised learning on the other hand is suitable when no output variables are needed. The only data needed are the inputs. In this type of learning, the system just keeps learning more about the inputs.
Special applications of supervised learning are in image recognition, speech recognition, financial analysis, neural networking, forecasting and a whole lot more.
Application of unsupervised learning is in pre-processing of data during exploratory analysis.
<em>Hope this helps!</em>
<span>One of the key elements in reducing the attack surface of an IT enterprise is to determine the location and sensitive nature of all data, especially privacy data which if compromised, could result in litigation, financial loss, or customer confidence loss. Additionally, this information is part of the foundation of when drafting a Disaster Recovery or Business Continuity plan.</span>
