By learning how to follow, one can be a good leader because: Looking up to a leader and following them help to:
- Keep one's ego in check and one can be able to be a good ego manager.
- They create strong credibility.
- They help use to focus our efforts for maximum impact.
<h3>How does being a good follower make you a good leader?</h3>
As a good follower, a person can be able to have the boldness and confidence to be able to respectfully talk about a lot of things with their leader if you see that you're not going in the right way.
Note that one can trust your leader and this will boast up the spirit of your input and engagement in all.
Hence, By learning how to follow, one can be a good leader because: Looking up to a leader and following them help to:
- Keep one's ego in check and one can be able to be a good ego manager.
- They create strong credibility.
- They help use to focus our efforts for maximum impact.
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Answer:
def course_grader(student_to_grades, course_prefix):
student_grades = dict()
for key, value in student_to_grades.items():
grade_score = 0
for course,grade in value.items():
if course_prefix == course:
grade_score += grade
student_grades[key] = grade_score / len(value.keys())
return student_grades
Explanation:
The course_grader function is a python program that accepts two arguments, the student dictionary and the course prefix. The function returns a dictionary of the student id as the key and the average grade of the student as the value.
Answer:
Kindly check Explanation.
Explanation:
Machine Learning refers to a concept of teaching or empowering systems with the ability to learn without explicit programming.
Supervised machine learning refers to a Machine learning concept whereby the system is provided with both features and label or target data to learn from. The target or label refers to the actual prediction which is provided alongside the learning features. This means that the output, target or label of the features used in training is provided to the system. this is where the word supervised comes in, the target or label provided during training or teaching the system ensures that the system can evaluate the correctness of what is she's being taught. The actual prediction provided ensures that the predictions made by the system can be monitored and accuracy evaluated.
Hence the main difference between supervised and unsupervised machine learning is the fact that one is provided with label or target data( supervised learning) and unsupervised learning isn't provided with target data, hence, it finds pattern in the data on it's own.
A to B mapping or input to output refers to the feature to target mapping.
Where A or input represents the feature parameters and B or output means the target or label parameter.
Answer:
true
Explanation:
web application is a software or program which is accessible using any web browser.
