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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender todo lo que necesitas saber acerca de autoML y Pycaret. Aprenderemos a generar un modelo predictivo de clasificación capaz de predecir el fraude bancario. Para ello, aprenderemos a generar múltiples modelos de ML y metamodelos, a evaluar su eficiencia, a desplegarlos en producción y a guardarlos en MlFlow, etc.
Register for this course and see more details by visiting:
OpenCourser.com/course/g90mtc/prediccion
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What's inside
Syllabus
Predicción del fraude bancario con autoML y Pycaret
En este curso se aprenderá a utilizar Pycaret para predecir el fraude bancario
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Cuenta con una estructura práctica y efectiva para facilitar el aprendizaje sobre autoML y Pycaret
Se enfoca en un caso de estudio relevante y aplicable: la predicción del fraude bancario
Proporciona una base sólida para comprender y aplicar técnicas de autoML con Pycaret
Apto para principiantes que buscan iniciarse en el campo del autoML y Pycaret
Save this course
Save Predicción del fraude bancario con autoML y Pycaret to your list so you can find it easily later:
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Reviews summary
Effective predictive modeling
The course is an effective hands-on course that covers the important aspects of predictive modeling for fraud detection.
Learn to predict fraudulent transactions.
"...clasificación capaz de predecir el fraude..."
Practical and effective for learning.
"This project is a course practical and effective..."
Course materials are locked after completion.
"...despues de unos días he intentado repasar el material, y mi sorpresa es que me solicita volver a pagar para poder repasar el material..."
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 Predicción del fraude bancario con autoML y Pycaret with these
activities:
Record and evaluate current knowledge
Show steps
Reinforce your knowledge of AutoML, Pycaret, and other related concepts you may have studied in previous courses
Browse courses on
AutoML
Show steps
Practice building predictive models using PyCaret
Show steps
Boost your proficiency in building predictive models with PyCaret through regular practice
Browse courses on
Pycaret
Show steps
-
Create a dataset and import it into PyCaret
-
Perform data preprocessing and feature engineering
-
Train and evaluate several machine learning models using PyCaret
Engage in peer-to-peer discussions
Show steps
Enhance your understanding through discussions and collaboration with peers
Browse courses on
AutoML
Show steps
-
Participate in online forums or discussion groups related to the course topic
-
Ask questions, share insights, and engage in constructive discussions
-
Provide feedback and support to fellow learners
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore additional tutorials and resources
Show steps
Expand your knowledge by exploring resources beyond the course material
Browse courses on
AutoML
Show steps
-
Identify reputable sources of tutorials and articles
-
Select tutorials that align with your learning goals
-
Work through the tutorials and apply the concepts
Develop a presentation
Show steps
Enhance your understanding of the course material by presenting it to others
Browse courses on
AutoML
Show steps
-
Choose a specific topic related to AutoML, PyCaret, or machine learning
-
Research and gather information on the chosen topic
-
Create presentation slides that effectively convey the information
-
Practice delivering the presentation and seek feedback
Develop a project using AutoML and PyCaret
Show steps
Apply your knowledge by building a project that demonstrates your skills in AutoML and PyCaret
Browse courses on
AutoML
Show steps
-
Identify a problem or challenge that can be addressed using AutoML and PyCaret
-
Gather and prepare the necessary data
-
Build and evaluate machine learning models using PyCaret
-
Deploy the best-performing model and monitor its performance
Record and evaluate current knowledge
Show steps
Reinforce your knowledge of AutoML, Pycaret, and other related concepts you may have studied in previous courses
Browse courses on
AutoML
Show steps
Show steps
Show steps
Practice building predictive models using PyCaret
Show steps
Boost your proficiency in building predictive models with PyCaret through regular practice
Browse courses on
Pycaret
Show steps
Show steps
Show steps
- Create a dataset and import it into PyCaret
- Perform data preprocessing and feature engineering
- Train and evaluate several machine learning models using PyCaret
Engage in peer-to-peer discussions
Show steps
Enhance your understanding through discussions and collaboration with peers
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Participate in online forums or discussion groups related to the course topic
- Ask questions, share insights, and engage in constructive discussions
- Provide feedback and support to fellow learners
Three other activities
Expand to see all activities and additional details
Show all six activities
Explore additional tutorials and resources
Show steps
Expand your knowledge by exploring resources beyond the course material
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Identify reputable sources of tutorials and articles
- Select tutorials that align with your learning goals
- Work through the tutorials and apply the concepts
Develop a presentation
Show steps
Enhance your understanding of the course material by presenting it to others
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Choose a specific topic related to AutoML, PyCaret, or machine learning
- Research and gather information on the chosen topic
- Create presentation slides that effectively convey the information
- Practice delivering the presentation and seek feedback
Develop a project using AutoML and PyCaret
Show steps
Apply your knowledge by building a project that demonstrates your skills in AutoML and PyCaret
Browse courses on
AutoML
Show steps
Show steps
Show steps
- Identify a problem or challenge that can be addressed using AutoML and PyCaret
- Gather and prepare the necessary data
- Build and evaluate machine learning models using PyCaret
- Deploy the best-performing model and monitor its performance
Career center
Learners who complete Predicción del fraude bancario con autoML y Pycaret will develop knowledge and skills
that may be useful to these careers:
Anti-Money Laundering Analyst
Anti-Money Laundering Analyst
Anti-Money Laundering Analysts investigate and prevent money laundering, and they use their knowledge of anti-money laundering techniques to identify and mitigate financial losses. This course can help you build a foundation for success as an Anti-Money Laundering Analyst by providing you with the skills and knowledge needed to detect and prevent money laundering.
Fraud Analyst
Fraud Analyst
Fraud Analysts investigate and prevent fraud, and they use their knowledge of fraud detection techniques to identify and mitigate financial losses. This course can help you build a foundation for success as a Fraud Analyst by providing you with the skills and knowledge needed to detect and prevent fraud.
Risk Analyst
Risk Analyst
Risk Analysts evaluate and manage risk, and they use their knowledge of risk management techniques to identify and mitigate financial losses. This course can help you build a foundation for success as a Risk Analyst by providing you with the skills and knowledge needed to manage risk.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their knowledge of machine learning to build and deploy machine learning models. This course can help you build a foundation for success as a Machine Learning Engineer by providing you with the skills and knowledge needed to build and deploy machine learning models.
Data Analyst
Data Analyst
Data Analysts use their programming and statistical knowledge to analyze large sets of data. They can work in a variety of industries, but the financial industry is a popular option for those with a background in fraud detection. The skills and knowledge learned in this course, such as using machine learning to predict fraud, can help you build a foundation for success as a Data Analyst.
Data Scientist
Data Scientist
Data Scientists use their knowledge of data science to solve business problems. This course can help you build a foundation for success as a Data Scientist by providing you with the skills and knowledge needed to collect, clean, and analyze data, and to build and deploy machine learning models.
Actuary
Actuary
Actuaries use their knowledge of mathematics and statistics to assess and manage risk. This course can help you build a foundation for success as an Actuary by providing you with the skills and knowledge needed to assess and manage risk.
Risk Manager
Risk Manager
Risk Managers identify and manage risk. This course can help you build a foundation for success as a Risk Manager by providing you with the skills and knowledge needed to identify and manage risk.
Information Security Analyst
Information Security Analyst
Information Security Analysts protect information systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course can help you build a foundation for success as an Information Security Analyst by providing you with the skills and knowledge needed to protect information systems from unauthorized access, use, disclosure, disruption, modification, or destruction.
Financial Analyst
Financial Analyst
Financial Analysts provide financial advice to individuals and businesses. This course can help you build a foundation for success as a Financial Analyst by providing you with the skills and knowledge needed to analyze financial data and make investment decisions.
Compliance Officer
Compliance Officer
Compliance Officers ensure that companies comply with laws and regulations. This course can help you build a foundation for success as a Compliance Officer by providing you with the skills and knowledge needed to ensure that companies comply with laws and regulations.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. This course can help you build a foundation for success as a Quantitative Analyst by providing you with the skills and knowledge needed to analyze and interpret financial data.
Auditor
Auditor
Auditors review financial records and provide assurance that financial statements are accurate and complete. This course can help you build a foundation for success as an Auditor by providing you with the skills and knowledge needed to review financial records and provide assurance that financial statements are accurate and complete.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help you build a foundation for success as a Software Engineer by providing you with the skills and knowledge needed to develop software systems.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to improve business processes. This course can help you build a foundation for success as a Business Analyst by providing you with the skills and knowledge needed to improve business processes.
For more career information including salaries, visit:
OpenCourser.com/course/g90mtc/prediccion
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
Predicción del fraude bancario con autoML y Pycaret.
Este libro proporciona una guía práctica para el aprendizaje automático utilizando Python, desde la preparación de datos hasta la implementación del modelo.
Save
Este libro ofrece una introducción integral al aprendizaje automático, cubre conceptos básicos, algoritmos y aplicaciones.
Este libro proporciona una guía práctica para el aprendizaje automático utilizando populares bibliotecas de Python como Scikit-Learn, Keras y TensorFlow.
Este libro es un texto integral sobre aprendizaje automático, cubre los conceptos teóricos y prácticos esenciales en profundidad.
Este libro ofrece una visión general accesible de la inteligencia artificial, cubriendo conceptos, algoritmos y sus implicaciones éticas.
Este libro es un recurso completo que cubre diversos aspectos del fraude, incluidas las técnicas de detección y prevención.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/g90mtc/prediccion
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Effort
2 horas
Level
Advanced
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Language
Español
Good to know
Cuenta con una estructura práctica y efectiva para facilitar el aprendizaje sobre autoML y Pycaret
Se enfoca en un caso de estudio relevante y aplicable: la predicción del fraude bancario
Proporciona una base sólida para comprender y aplicar técnicas de autoML con Pycaret
Apto para principiantes que buscan iniciarse en el campo del autoML y Pycaret
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