Participants in open source community projects get experience and make connections with other professionals that can be valuable resources during a job hunt.
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>
Answer:
Explanation:
pop(): Remove an item from the end of an array
push(): Add items to the end of an array
shift(): Remove an item from the beginning of an array
unshift(): Add items to the beginning of an array
IF function has three parts
IF (condition_to_check , return_if_true , return_if_false)
IF function first checks condition. If it is true it returns first result. Otherwise it returns second result.
Condition to check:
B3>D5
After inserting numbers we get:
10>8
This is correct so the first result will be returned.
The given IF function returns "Closed".
Answer:
attenuation
Explanation:
Based on the information provided within the question it can be said that the phenomenon that is being described in this scenario is known as attenuation. In the context of physics, this refers to the gradual loss of intensity of something when traveling through a medium. Which in this case would be the data signals travelling through the cables.
