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Incorrect predictions by classification

Learn how to consider errors in predictions sensibly
0.0
0.0/5
(0 reviews)
1 students
Created by Wim Koevoets

9.0

CourseMarks Score®

10.0

Freshness

N/A

Feedback

7.6

Content

Platform: Udemy
Price: $11.99
Video: 47m
Language: English
Next start: On Demand

Top Predictive Modeling courses:

Detailed Analysis

CourseMarks Score®

9.0 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

10.0 / 10
This course was last updated on 4/2021.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

We analyzed factors such as the rating (0.0/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

7.6 / 10
Video Score: 7.7 / 10
The course includes 47m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 2 hours 03 minutes of 5 Predictive Modeling courses on Udemy.
Detail Score: 9.7 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 5.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
0 resource.
0 exercise.
0 test.

Table of contents

Description

Use this course to bring your thinking about prediction errors to a practical level. With prediction by classification different types of prediction errors have different practical implications. Understand these differences to better build and assess the relevance of your predictions.
Understand the Trade-Offs between Prediction Errors
•Learn what is classification and the reasons for using it.
•Recognize the use of classification for prediction in technologies around you.
•Understand classification to predict and why prediction errors appear.
•Learn to think about the practical implications of prediction errors.
•Learn when aiming for no prediction errors is not a good idea.
See the Practical Relevance of Predictions
Technologies that use classification for prediction include E-mail spam filters, systems to detect suspicious purchases with your bank card and self-driving cars. Data scientists and their colleagues work with large amounts of data to make these technologies successful. This course aims at developing your intuition on the practical relevance of predictions. The absence of programming examples and mathematical detail is a key feature of this course.
The practical implications of classification prediction errors tend to receive no or little attention in courses or textbooks discussing machine learning classification methods. This course focusses on those implications and provides guidance on what to do when knowing them.

The course starts with defining classification and provides simple examples. It explains statistical classification and that uncertainty adds complexity to classification problems. It provides reasons for why people use classification methods and prediction is the reason that is central to this course. You will learn the main ideas about predictions and methods to make them.

Six different real-life applications of prediction by classification are around us or will be around us in the not-so-distant-future. You will understand the characteristics they share with each other and two of the applications will be discussed in detail throughout the course.
You will learn also why the presence of prediction errors is to an extent inevitable and how to use knowledge about their practical implications to your advantage. In addition, you will learn about some practical aspects in prediction projects related to prediction errors. One of them is the issue of setting almost zero prediction errors as your goal.

Requirements

• Numeric skills including interpreting a ratio of two numbers
• Be able to interpret graphs and charts
• Be able to interpret numbers in a table

You will learn

✓ Classification and the reasons for using it.
✓ Technologies around you that use classification for prediction.
✓ What features those technologies have in common.
✓ Why prediction errors appear.
✓ Thinking about the practical implications of prediction errors.
✓ Why aiming for no prediction errors may not always be a good idea.

This course is for

• Data scientists, their colleagues and people curious about improving the practical relevance of prediction using classification methods.

How much does the Incorrect predictions by classification course cost? Is it worth it?

The course costs $11.99. And currently there is a 52% discount on the original price of the course, which was $24.99. So you save $13 if you enroll the course now.
The average price is $13.6 of 5 Predictive Modeling courses. So this course is 12% cheaper than the average Predictive Modeling course on Udemy.

Does the Incorrect predictions by classification course have a money back guarantee or refund policy?

YES, Incorrect predictions by classification has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Incorrect predictions by classification course, but there is a $13 discount from the original price ($24.99). So the current price is just $11.99.

Who is the instructor? Is Wim Koevoets a SCAM or a TRUSTED instructor?

Wim Koevoets has created 1 courses that got 0 reviews which are generally positive. Wim Koevoets has taught 1 students and received a average review out of 0 reviews. Depending on the information available, Wim Koevoets is a TRUSTED instructor.

More info about the instructor, Wim Koevoets

Applied statistics and econometrics, data science
I am specialized in applying statistics and economics to data sets with observations on real phenomena.After undergraduate training in mathematical statistics and econometrics I started doing this 25 years ago. I have a PhD in applied econometrics and an AWS Machine Learning certificate. I applied statistics and econometrics in projects for governments and international microeconomics consulting firms.I continue learning about new developments in applied data analysis. By teaching, I aim at sharing my experience and the insights it gave me with you. I enjoy explaining things in a way such that you understand them, understand them better, can do them, can do them better or see them from a new perspective.

9.0

CourseMarks Score®

10.0

Freshness

N/A

Feedback

7.6

Content

Platform: Udemy
Price: $11.99
Video: 47m
Language: English
Next start: On Demand

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