Using the computer language in python to write a function code that personalized house signs
<h3>Writting the code in python:</h3>
<em>#Assign varibles</em>
<em>charge = 0.00</em>
<em>numChars = 8</em>
<em>color = "gold"</em>
<em>woodType = "oak"</em>
<em />
<em>#Checking for number of characters</em>
<em>if numChars > 5:</em>
<em>charge = 35 + (numChars-5)*4</em>
<em>elif numChars > 0:</em>
<em>charge = 35</em>
<em />
<em>#Checking wood type</em>
<em>if woodType == "oak":</em>
<em>charge += 20</em>
<em />
<em>#Checking for color</em>
<em>if color == "gold":</em>
<em>charge += 15</em>
<em />
<em>#Print output</em>
<em>print("The charge for this sign is $"+str(charge)+".")</em>
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Answer:
I guess if there is experiment going on in absence one of those furniture then the experiment isn't successful
It can have only 16,384 number of columns
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>
