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Dr. Meg Bertoni
How does your toaster know what “darker” means and what to do about it? Fuzzy logic is the foundation of how machines synthesize human understanding of qualitative values.
By the end of this project, learners will discover how fuzzy logic works using set...
Read more
How does your toaster know what “darker” means and what to do about it? Fuzzy logic is the foundation of how machines synthesize human understanding of qualitative values.
By the end of this project, learners will discover how fuzzy logic works using set...
Read more
How does your toaster know what “darker” means and what to do about it? Fuzzy logic is the foundation of how machines synthesize human understanding of qualitative values.
By the end of this project, learners will discover how fuzzy logic works using set theory, and create machine-learning analyses of datasets using the Google Sheets add-on BigML.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/qdkfz9/simulate
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Explores fuzzy logic's applications in machine understanding, a field highly relevant to computer science and artificial intelligence
Guided by an experienced instructor, Dr. Meg Bertoni, known for their work in fuzzy logic
Provides hands-on experience using Google Sheets add-on BigML for machine-learning analyses, ensuring practical skill development
Suitable for North America-based learners, potentially limiting accessibility for others
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Save Simulate Machine Intel w/Fuzzy Logic, Google Sheets & BigML to your list so you can find it easily later:
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Reviews summary
Fuzzy logic in machine learning
This course gives a basic introduction to fuzzy logic and its use in machine learning with Google Sheets and BigML. It is most suitable for North American learners. While many were initially expecting more of the course, it can be helpful to those who want to learn the basics.
Introduces concepts and tools of fuzzy logic.
"Es un curso que muestra los conceptos y herramientas básicas para iniciar con Logica difusa"
Google Sheets and BigML are not essential to the course.
"If google sheets and BigML were not in the course nothing would be different..."
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 Simulate Machine Intel w/Fuzzy Logic, Google Sheets & BigML with these
activities:
Review Set Theory
Show steps
Establish a strong foundation for core concepts used in fuzzy logic.
Show steps
-
Review the definitions and representations of sets.
-
Practice identifying and constructing set diagrams.
-
Explore the different set operations (union, intersection, complement).
-
Apply set theory to solve simple real-world problems.
Guided Exercises on Fuzzy Logic Principles
Show steps
Develop a solid understanding of the mechanics and computational aspects of fuzzy logic.
Browse courses on
Fuzzy Logic
Show steps
-
Follow step-by-step tutorials on fuzzy logic operations.
-
Attempt practice exercises to apply fuzzy logic principles.
-
Create small programs or scripts to implement fuzzy logic algorithms.
Attend industry workshops or conferences on fuzzy logic applications
Show steps
Gain exposure to the latest advancements and industry trends.
Show steps
-
Research upcoming workshops or conferences related to fuzzy logic.
-
Register and attend the event.
-
Engage with experts, learn from presentations, and network with professionals.
One other activity
Expand to see all activities and additional details
Show all four activities
Develop Visualizations to Explain Fuzzy Logic Concepts
Show steps
Enhance comprehension and communication of fuzzy logic concepts by translating them into visual representations.
Browse courses on
Data Visualization
Show steps
-
Identify key fuzzy logic concepts to visualize.
-
Choose appropriate data visualization techniques to represent the concepts.
-
Create clear and concise visualizations that effectively communicate the concepts.
-
Present the visualizations to explain fuzzy logic to others.
Review Set Theory
Show steps
Establish a strong foundation for core concepts used in fuzzy logic.
Show steps
Show steps
Show steps
- Review the definitions and representations of sets.
- Practice identifying and constructing set diagrams.
- Explore the different set operations (union, intersection, complement).
- Apply set theory to solve simple real-world problems.
Guided Exercises on Fuzzy Logic Principles
Show steps
Develop a solid understanding of the mechanics and computational aspects of fuzzy logic.
Browse courses on
Fuzzy Logic
Show steps
Show steps
Show steps
- Follow step-by-step tutorials on fuzzy logic operations.
- Attempt practice exercises to apply fuzzy logic principles.
- Create small programs or scripts to implement fuzzy logic algorithms.
Attend industry workshops or conferences on fuzzy logic applications
Show steps
Gain exposure to the latest advancements and industry trends.
Show steps
Show steps
Show steps
- Research upcoming workshops or conferences related to fuzzy logic.
- Register and attend the event.
- Engage with experts, learn from presentations, and network with professionals.
One other activity
Expand to see all activities and additional details
Show all four activities
Develop Visualizations to Explain Fuzzy Logic Concepts
Show steps
Enhance comprehension and communication of fuzzy logic concepts by translating them into visual representations.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify key fuzzy logic concepts to visualize.
- Choose appropriate data visualization techniques to represent the concepts.
- Create clear and concise visualizations that effectively communicate the concepts.
- Present the visualizations to explain fuzzy logic to others.
Career center
Learners who complete Simulate Machine Intel w/Fuzzy Logic, Google Sheets & BigML will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. This course helps build a foundation in fuzzy logic, a field that is commonly used to develop machine learning algorithms for tasks such as natural language processing and image recognition.
Data Scientist
Data Scientist
Data Scientists apply statistical methods, programming skills, and machine learning algorithms to extract insights from data to help businesses make data-driven decisions. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML provides a foundation in machine learning analysis, using the Google Sheets add-on BigML, which can be particularly useful for Data Scientists who seek to leverage Google Sheets in their work.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML can be useful for Data Analysts who seek to develop their skills in machine learning analysis and data visualization.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a foundation in machine learning analysis, which can be useful for Software Engineers who work on developing machine learning-based applications.
Business Analyst
Business Analyst
Business Analysts analyze business processes and data to help businesses improve their performance. This course provides a foundation in machine learning analysis, which can be useful for Business Analysts who work on developing data-driven solutions.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical modeling to analyze financial data and make investment decisions. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML can be useful for Quantitative Analysts who seek to develop their skills in machine learning analysis and data visualization.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex business problems. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML can be useful for Operations Research Analysts who seek to develop their skills in machine learning analysis and data visualization.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to understand consumer behavior and market trends. This course provides a foundation in machine learning analysis, which can be useful for Market Researchers who work on developing data-driven marketing strategies.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses and organizations make informed decisions. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML can be useful for Statisticians who seek to develop their skills in machine learning analysis and data visualization.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment decisions. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML can be useful for Financial Analysts who seek to develop their skills in machine learning analysis and data visualization.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines to support data analytics and machine learning applications. This course provides a foundation in machine learning analysis, which can be useful for Data Engineers who work on developing machine learning-based data pipelines.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess and manage risk. This course provides a foundation in machine learning analysis, which can be useful for Actuaries who work on developing risk assessment models.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML may be useful for Project Managers who seek to develop their skills in machine learning analysis and data visualization, which can be helpful for managing project risks and dependencies.
Risk Manager
Risk Manager
Risk Managers identify, assess, and manage risks to an organization. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML may be useful for Risk Managers who seek to develop their skills in machine learning analysis and data visualization, which can be helpful for developing risk assessment models and managing risk.
Product Manager
Product Manager
Product Managers oversee the development and launch of new products. This course in Simulating Machine Intelligence with Fuzzy Logic, Google Sheets, and BigML may be useful for Product Managers who seek to develop their skills in machine learning analysis and data visualization, which can be helpful for understanding customer needs and developing data-driven product strategies.
For more career information including salaries, visit:
OpenCourser.com/course/qdkfz9/simulate
Reading list
We've selected six 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
Simulate Machine Intel w/Fuzzy Logic, Google Sheets & BigML.
Provides a comprehensive overview of fuzzy logic, covering both the theoretical foundations and practical applications. It is an excellent resource for those who want to learn more about the use of fuzzy logic in various fields.
Provides a comprehensive overview of Python, a programming language that is commonly used for data analysis. It covers the basics of Python programming, as well as how to use Python for data analysis tasks.
Provides a comprehensive overview of R, a programming language that is commonly used for data analysis and machine learning. It covers the basics of R programming, as well as how to use R for machine learning tasks.
Provides a comprehensive overview of machine learning with Python. It covers the basics of machine learning, as well as how to use Python for machine learning tasks.
Provides a gentle introduction to machine learning for those who are new to the field. It covers the basics of machine learning, as well as how to use Python for machine learning tasks.
Save
Provides a comprehensive overview of Google Sheets for business users. It covers the basics of spreadsheet usage, as well as how to use Google Sheets for business applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qdkfz9/simulate
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Dr. Meg Bertoni
Good to know
Explores fuzzy logic's applications in machine understanding, a field highly relevant to computer science and artificial intelligence
Guided by an experienced instructor, Dr. Meg Bertoni, known for their work in fuzzy logic
Provides hands-on experience using Google Sheets add-on BigML for machine-learning analyses, ensuring practical skill development
Suitable for North America-based learners, potentially limiting accessibility for others
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