
Местные курсы Python skope-rules под руководством местных инструкторов в Russia.
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I like to combine the actual ML application scenarios.
交银康联
Курсы: Machine Learning with Rules using Python skope-rules
practical part
Magdalena Orzędowska-Kubeczak - EduBroker Sp. z o.o.
Курсы: IBM ODM Decision Management
Answers to questions, consultations
EduBroker Sp. z o.o.
Курсы: IBM ODM Decision Management
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EduBroker Sp. z o.o.
Курсы: IBM ODM Decision Management
Python skope-rules Содержание курса
Название курса
Продолжительность
Обзор
Название курса
Продолжительность
Обзор
14 часов
Обзор
This course introduces the student to the Python language. Upon completion of this class, the student will be able to write non trivial Python programs dealing with a wide variety of subject matter domains. Topics include language components, working with a professional IDE, control flow constructs, strings, I/O, collections, classes, modules, and regular expressions. The course is supplemented with many hands-on labs, solutions, and code examples.
After Completing the course students will be able to demonstrate knowledge and understanding of Python Security Principles.
After Completing the course students will be able to demonstrate knowledge and understanding of Python Security Principles.
14 часов
Обзор
Skope-rules is a Python machine learning module built on top of scikit-learn.
In this instructor-led, live training (onsite or remote), participants will learn how to use Python skope-rules to automatically generate rules based on existing data sets.
By the end of this training, participants will be able to:
- Use skope-rules to extract rules from available data.
- Apply skope-rules to carry out classification, particularly useful in supervised anomaly detection, or imbalanced classification.
- Generate rules for classifying new incoming data.
- Fit rules to address real-world problems in fraud detection, predictive maintenance, intrusion detection, insurance application approvals, etc.
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice in a live-lab environment.
Note
- To request a customized training for this course, please contact us to arrange.
- To learn more about skope-rules, please visit: https://github.com/scikit-learn-contrib/skope-rules
In this instructor-led, live training (onsite or remote), participants will learn how to use Python skope-rules to automatically generate rules based on existing data sets.
By the end of this training, participants will be able to:
- Use skope-rules to extract rules from available data.
- Apply skope-rules to carry out classification, particularly useful in supervised anomaly detection, or imbalanced classification.
- Generate rules for classifying new incoming data.
- Fit rules to address real-world problems in fraud detection, predictive maintenance, intrusion detection, insurance application approvals, etc.
Format of the Course
- Part lecture, part discussion, exercises and heavy hands-on practice in a live-lab environment.
Note
- To request a customized training for this course, please contact us to arrange.
- To learn more about skope-rules, please visit: https://github.com/scikit-learn-contrib/skope-rules
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