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Ryan Ahmed
In this project, we will predict Ads clicks using logistic regression and XG-boost algorithms. In this project, we will assume that you have been hired as a consultant to a start-up that is running a targeted marketing ad campaign on Facebook. The company wants to analyze customer behavior by predicting which customer clicks on the advertisement.
Register for this course and see more details by visiting:
OpenCourser.com/course/amw3yw/predict
What's inside
Syllabus
Project Overview
In this project, we will predict Ads clicks using logistic regression and XG-boost algorithms. In this project, we will assume that you have been hired as a consultant to a start-up that is running a targeted marketing ad campaign on Facebook. The company wants to analyze customer behavior by predicting which customer clicks on the advertisement.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
May appeal to marketers and other marketing professionals, as it covers customer behavior and ad performance
Introduces learners to logistic regression and XG-boost algorithms
Assumes learners have been hired as consultants for a start-up, providing real-world context
Led by instructors with expertise in marketing and data science
Requires a strong foundation in statistics and machine learning
May not be suitable for beginners in data science or marketing
Save this course
Save Predict Ad Clicks Using Logistic Regression and XG-Boost to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Predict Ad Clicks Using Logistic Regression and XG-Boost with these
activities:
Review Your Notes on Logistic Regression
Show steps
Reviewing your notes will help you refresh your memory on the key concepts of logistic regression before starting the course.
Browse courses on
Logistic Regression
Show steps
-
Gather your notes on logistic regression.
-
Review the notes and make sure you understand the concepts.
Read 'Data Science for Business'
Show steps
Review the fundamentals of data science to strengthen your understanding of the concepts used in this course.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
-
Read the first three chapters of the book to get an overview of data science concepts.
-
Complete the practice exercises at the end of each chapter to test your understanding.
Solve Logistic Regression Practice Problems
Show steps
Practice solving logistic regression problems to improve your understanding of the algorithm and its applications.
Browse courses on
Logistic Regression
Show steps
-
Find a set of practice problems online or in a textbook.
-
Solve the problems and check your answers.
-
Review the solutions and identify any errors or areas where you need more practice.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Work on XG-Boost Practice Problems
Show steps
Practice solving XG-Boost problems to improve your understanding of the algorithm and its applications.
Browse courses on
XG-Boost
Show steps
-
Find a set of practice problems online or in a textbook.
-
Solve the problems and check your answers.
-
Review the solutions and identify any errors or areas where you need more practice.
Design an Infographic on XG-Boost
Show steps
Creating an infographic will help you visualize and communicate the key concepts of XG-Boost.
Browse courses on
XG-Boost
Show steps
-
Gather the key information about XG-Boost.
-
Choose a design template or create your own.
-
Add visuals and text to your infographic.
-
Edit and proofread your infographic.
-
Share your infographic with others.
Create a Tutorial Explaining Logistic Regression
Show steps
Creating a tutorial will help you solidify your understanding of logistic regression and improve your communication skills.
Browse courses on
Logistic Regression
Show steps
-
Plan the structure and content of your tutorial.
-
Write the content for your tutorial.
-
Create any necessary visuals or examples to support your explanations.
-
Edit and proofread your tutorial.
-
Share your tutorial with others.
Mentor a Junior Data Scientist
Show steps
Mentoring a junior data scientist will help you reinforce your knowledge and gain valuable leadership experience.
Show steps
-
Find a junior data scientist who is looking for a mentor.
-
Set up regular meetings to discuss their progress and provide guidance.
-
Help them identify resources and opportunities for professional development.
-
Provide feedback on their work and offer encouragement.
Contribute to an Open-Source Data Science Project
Show steps
Contributing to an open-source project will give you hands-on experience and allow you to learn from others.
Browse courses on
Open Source
Show steps
-
Identify an open-source data science project that you are interested in.
-
Find a way to contribute to the project, such as fixing a bug or adding a new feature.
-
Submit a pull request with your changes.
-
Work with the project maintainers to get your changes merged.
Review Your Notes on Logistic Regression
Show steps
Reviewing your notes will help you refresh your memory on the key concepts of logistic regression before starting the course.
Browse courses on
Logistic Regression
Show steps
Show steps
Show steps
- Gather your notes on logistic regression.
- Review the notes and make sure you understand the concepts.
Read 'Data Science for Business'
Show steps
Review the fundamentals of data science to strengthen your understanding of the concepts used in this course.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read the first three chapters of the book to get an overview of data science concepts.
- Complete the practice exercises at the end of each chapter to test your understanding.
Solve Logistic Regression Practice Problems
Show steps
Practice solving logistic regression problems to improve your understanding of the algorithm and its applications.
Browse courses on
Logistic Regression
Show steps
Show steps
Show steps
- Find a set of practice problems online or in a textbook.
- Solve the problems and check your answers.
- Review the solutions and identify any errors or areas where you need more practice.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Work on XG-Boost Practice Problems
Show steps
Practice solving XG-Boost problems to improve your understanding of the algorithm and its applications.
Browse courses on
XG-Boost
Show steps
Show steps
Show steps
- Find a set of practice problems online or in a textbook.
- Solve the problems and check your answers.
- Review the solutions and identify any errors or areas where you need more practice.
Design an Infographic on XG-Boost
Show steps
Creating an infographic will help you visualize and communicate the key concepts of XG-Boost.
Browse courses on
XG-Boost
Show steps
Show steps
Show steps
- Gather the key information about XG-Boost.
- Choose a design template or create your own.
- Add visuals and text to your infographic.
- Edit and proofread your infographic.
- Share your infographic with others.
Create a Tutorial Explaining Logistic Regression
Show steps
Creating a tutorial will help you solidify your understanding of logistic regression and improve your communication skills.
Browse courses on
Logistic Regression
Show steps
Show steps
Show steps
- Plan the structure and content of your tutorial.
- Write the content for your tutorial.
- Create any necessary visuals or examples to support your explanations.
- Edit and proofread your tutorial.
- Share your tutorial with others.
Mentor a Junior Data Scientist
Show steps
Mentoring a junior data scientist will help you reinforce your knowledge and gain valuable leadership experience.
Show steps
Show steps
Show steps
- Find a junior data scientist who is looking for a mentor.
- Set up regular meetings to discuss their progress and provide guidance.
- Help them identify resources and opportunities for professional development.
- Provide feedback on their work and offer encouragement.
Contribute to an Open-Source Data Science Project
Show steps
Contributing to an open-source project will give you hands-on experience and allow you to learn from others.
Browse courses on
Open Source
Show steps
Show steps
Show steps
- Identify an open-source data science project that you are interested in.
- Find a way to contribute to the project, such as fixing a bug or adding a new feature.
- Submit a pull request with your changes.
- Work with the project maintainers to get your changes merged.
Career center
Learners who complete Predict Ad Clicks Using Logistic Regression and XG-Boost will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Data Scientist perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Data Scientist's belt that they can use to increase their project impact at their company.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Machine Learning Engineer perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Machine Learning Engineer's belt that they can use to increase their project impact at their company.
Business Analyst
Business Analyst
A Business Analyst will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Business Analyst perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Business Analyst's belt that they can use to increase their project impact at their company.
Software Engineer
Software Engineer
A Software Engineer will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Software Engineer perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Software Engineer's belt that they can use to increase their project impact at their company.
Data Analyst
Data Analyst
A Data Analyst will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Data Analyst perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Data Analyst's belt that they can use to increase their project impact at their company.
Marketing Analyst
Marketing Analyst
A Marketing Analyst will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Marketing Analyst perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Marketing Analyst's belt that they can use to increase their project impact at their company.
Customer Success Manager
Customer Success Manager
A Customer Success Manager will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Customer Success Manager perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Customer Success Manager's belt that they can use to increase their project impact at their company.
Market Researcher
Market Researcher
A Market Researcher will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Market Researcher perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Market Researcher's belt that they can use to increase their project impact at their company.
User Experience (UX) Researcher
User Experience (UX) Researcher
A User Experience (UX) Researcher will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a User Experience (UX) Researcher perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a User Experience (UX) Researcher's belt that they can use to increase their project impact at their company.
Consultant
Consultant
A Consultant will learn the basics of predicting customer behavior to help their clients understand what drives their customers' decisions. This course can help a Consultant perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Consultant's belt that they can use to increase their project impact at their company.
Data Engineer
Data Engineer
A Data Engineer will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Data Engineer perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Data Engineer's belt that they can use to increase their project impact at their company.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst will learn the basics of predicting customer behavior to help their company understand what drives their customers' decisions. This course can help a Quantitative Analyst perform regression and boosting algorithms that help to determine which features are most important for driving customer behavior. This will add another tool to a Quantitative Analyst's belt that they can use to increase their project impact at their company.
Product Manager
Product Manager
A Product Manager must understand customer behavior to create products that meet customer needs. This course can help a Product Manager understand the features that drive customer behavior, which can help them prioritize features and make better product decisions.
Growth Marketer
Growth Marketer
A Growth Marketer must understand customer behavior to create marketing campaigns that drive growth. This course can help a Growth Marketer understand the features that drive customer behavior, which can help them create more effective marketing campaigns.
Product Marketer
Product Marketer
A Product Marketer must understand customer behavior to create marketing campaigns that target the right customers. This course can help a Product Marketer understand the features that drive customer behavior, which can help them create more effective marketing campaigns.
For more career information including salaries, visit:
OpenCourser.com/course/amw3yw/predict
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Predict Ad Clicks Using Logistic Regression and XG-Boost.
Provides a comprehensive overview of statistical learning methods, including logistic regression and decision trees. It valuable resource for understanding the theoretical foundations of the algorithms used in the course.
Provides a hands-on introduction to machine learning using Python. It covers a wide range of topics, including data preprocessing, model training, and evaluation. It good resource for getting started with machine learning in Python.
Save
Provides a comprehensive overview of data mining techniques, including logistic regression and decision trees. It valuable resource for understanding the practical aspects of data mining.
Provides a comprehensive overview of machine learning using R. It covers a wide range of topics, including data preprocessing, model training, and evaluation. It good resource for getting started with machine learning in R.
Provides a practical introduction to machine learning using Python. It covers a wide range of topics, including data preprocessing, model training, and evaluation. It good resource for getting started with machine learning in Python.
Save
Provides a comprehensive overview of deep learning, including its theoretical foundations and practical applications. It good resource for gaining a deeper understanding of deep learning.
Save
Provides a comprehensive overview of machine learning algorithms. It good resource for gaining a deeper understanding of the algorithms used in machine learning.
Provides a comprehensive overview of the mathematics used in machine learning. It good resource for gaining a deeper understanding of the mathematical foundations of machine learning.
Provides a comprehensive overview of statistical methods used in machine learning. It good resource for gaining a deeper understanding of the statistical foundations of machine learning.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It good resource for gaining a deeper understanding of the probabilistic foundations of machine learning.
Provides a comprehensive overview of Bayesian reasoning and its applications in machine learning. It good resource for gaining a deeper understanding of the Bayesian foundations of machine learning.
Provides a hands-on introduction to machine learning for hackers. It covers a wide range of topics, including data preprocessing, model training, and evaluation. It good resource for getting started with machine learning for hackers.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/amw3yw/predict
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
May appeal to marketers and other marketing professionals, as it covers customer behavior and ad performance
Introduces learners to logistic regression and XG-boost algorithms
Assumes learners have been hired as consultants for a start-up, providing real-world context
Led by instructors with expertise in marketing and data science
Requires a strong foundation in statistics and machine learning
May not be suitable for beginners in data science or marketing
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