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Descubriendo anomalías con Azure Anomaly Detector
Nestor Nicolas Campos Rojas
Nestor Nicolas Campos Rojas
En este proyecto de 1 hora, aprenderás a utilizar el servicio cognitivo de Azure, Anomaly Detector, para detectar anomalías en datos temporales utilizando Inteligencia Artificial.
Read more
En este proyecto de 1 hora, aprenderás a utilizar el servicio cognitivo de Azure, Anomaly Detector, para detectar anomalías en datos temporales utilizando Inteligencia Artificial.
Read more
En este proyecto de 1 hora, aprenderás a utilizar el servicio cognitivo de Azure, Anomaly Detector, para detectar anomalías en datos temporales utilizando Inteligencia Artificial.
Además, podrás llamar al servicio utilizando PowerBI y el lenguaje M.
Register for this course and see more details by visiting:
OpenCourser.com/course/z1icff/descubriendo
What's inside
Syllabus
Descubriendo anomalías con Azure Anomaly Detector
Al final de este proyecto, tú podrás utilizar uno de los servicios cognitivos más simples pero poderosos de Azure, el detector de anomalías en datos temporales (Anomaly Detector).
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Desarrolla habilidades en detección de anomalías e integración con Power BI
Enseña un servicio cognitivo simple pero potente de Azure: Anomaly Detector
Requiere conocimientos previos en Power BI y lenguaje M
Se enfoca en datos temporales, limitando su aplicabilidad a otros tipos de datos
La duración del proyecto es de solo 1 hora, lo que puede ser insuficiente para una comprensión profunda
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Activities
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Descubriendo anomalías con Azure Anomaly Detector.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Descubriendo anomalías con Azure Anomaly Detector will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists combine programming skills, math, and statistical knowledge to extract insights from data. A crucial aspect of data science involves detecting anomalies and identifying patterns, which the Azure Anomaly Detector facilitates by automating the process and enhancing accuracy. With the Azure Anomaly Detector, Data Scientists can explore vast data sets more efficiently, uncovering hidden insights and making informed decisions.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve real-world problems. Detecting anomalies is a common task in machine learning, as it helps identify data points that deviate from the expected pattern. The Azure Anomaly Detector provides Machine Learning Engineers with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of model development and deployment.
Fraud Analyst
Fraud Analyst
Fraud Analysts investigate and prevent fraudulent activities within organizations. Detecting anomalies is crucial for Fraud Analysts, as it allows them to identify unusual patterns or transactions that may indicate fraudulent behavior. The Azure Anomaly Detector provides Fraud Analysts with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of fraud detection and prevention efforts.
Risk Analyst
Risk Analyst
Risk Analysts identify, assess, and mitigate risks within organizations. Detecting anomalies is a key component of risk management, as it helps identify potential threats or vulnerabilities. The Azure Anomaly Detector provides Risk Analysts with a powerful tool for automating anomaly detection, enabling them to proactively identify and mitigate risks, ensuring business continuity and resilience.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts (Quants) develop and implement mathematical and statistical models to analyze financial data and make investment recommendations. The ability to detect anomalies is essential for Quants, as it allows them to identify unusual patterns and trends that may indicate market inefficiencies or potential risks. The Azure Anomaly Detector provides Quants with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of their analyses.
Security Analyst
Security Analyst
Security Analysts monitor and protect computer systems and networks from cyber threats. Detecting anomalies is essential for Security Analysts, as it allows them to identify unusual patterns or activities that may indicate a security breach or attack. The Azure Anomaly Detector provides Security Analysts with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of threat detection and response.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases to ensure data integrity and performance. Detecting anomalies is essential for Database Administrators, as it helps identify data corruption, hardware failures, or other problems that may impact database reliability. The Azure Anomaly Detector provides Database Administrators with a valuable tool for automating anomaly detection, ensuring data integrity and database uptime.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines and infrastructure. Detecting anomalies is essential for Data Engineers, as it helps identify data quality issues, system failures, or other problems that may impact data integrity. The Azure Anomaly Detector provides Data Engineers with a valuable tool for automating anomaly detection, ensuring data quality and system reliability.
Data Analyst
Data Analyst
Data Analysts uncover insights by analyzing data and translating it into actionable information. Data from a variety of sources can be analyzed using the Azure Anomaly Detector, a valuable tool for the Data Analyst role. The Azure Anomaly Detector helps Data Analysts identify unusual patterns and trends in data, enabling them to pinpoint areas that require attention and make data-driven recommendations.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. Detecting anomalies is important for Software Engineers, as it helps identify bugs, performance issues, or other problems that may impact software quality. The Azure Anomaly Detector provides Software Engineers with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of software testing and debugging.
Business Analyst
Business Analyst
Business Analysts help companies identify opportunities for improvement and make data-driven decisions. They often use data analysis to identify trends and patterns. The Azure Anomaly Detector provides Business Analysts with a powerful tool for detecting anomalies and uncovering hidden insights in data, enabling them to make informed recommendations and drive business growth.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess and manage risk and uncertainty. Detecting anomalies is essential for Actuaries, as it helps identify unusual patterns or trends that may impact risk assessment and insurance pricing. The Azure Anomaly Detector provides Actuaries with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of risk assessment and insurance pricing.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve complex business problems. Detecting anomalies is important for Operations Research Analysts, as it helps identify inefficiencies, bottlenecks, or other problems that may impact business operations. The Azure Anomaly Detector provides Operations Research Analysts with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of problem-solving and optimization.
Financial Analyst
Financial Analyst
Financial Analysts evaluate and make recommendations on investments and financial decisions. Detecting anomalies is important for Financial Analysts, as it helps identify unusual patterns or trends that may impact investment performance. The Azure Anomaly Detector provides Financial Analysts with a valuable tool for automating anomaly detection, enhancing the accuracy and efficiency of investment analysis and decision-making.
IT Manager
IT Manager
IT Managers plan, implement, and manage IT systems and infrastructure. Detecting anomalies is essential for IT Managers, as it helps identify system failures, performance issues, or other problems that may impact IT service delivery. The Azure Anomaly Detector provides IT Managers with a valuable tool for automating anomaly detection, ensuring system reliability and service uptime.
For more career information including salaries, visit:
OpenCourser.com/course/z1icff/descubriendo
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
Descubriendo anomalías con Azure Anomaly Detector.
Save
This classic textbook provides a comprehensive overview of time series analysis, including methods for detecting and forecasting anomalies.
Este libro proporciona una base sólida en análisis de series temporales, los fundamentos estadísticos y los métodos para detectar anomalías en datos temporales. Es una lectura valiosa para quienes buscan profundizar su comprensión de la detección de anomalías.
Este libro proporciona una base sólida en aprendizaje automático, cubriendo conceptos fundamentales y algoritmos utilizados en la detección de anomalías. Es una lectura valiosa para quienes buscan comprender los fundamentos teóricos de la detección de anomalías.
Save
Este libro cubre técnicas de minería de datos, incluyendo métodos para detectar patrones y anomalías en grandes conjuntos de datos. Es una lectura valiosa para quienes buscan una visión general de los algoritmos y técnicas de detección de anomalías.
Este libro proporciona una base sólida en reconocimiento de patrones y aprendizaje automático, cubriendo algoritmos y técnicas utilizados en la detección de anomalías. Es una lectura valiosa para quienes buscan una comprensión más profunda de los fundamentos de la detección de anomalías.
Este libro proporciona una introducción concisa a los algoritmos de aprendizaje automático, cubriendo los conceptos fundamentales y los algoritmos utilizados en la detección de anomalías. Es una lectura valiosa para quienes buscan una comprensión básica de los fundamentos de la detección de anomalías.
Provides a comprehensive overview of anomaly detection in data mining, including different types of anomalies and techniques for detecting them.
Provides a comprehensive overview of time series forecasting and anomaly detection using the R programming language.
Save
Provides a comprehensive overview of anomaly detection in streaming data, including different types of anomalies and techniques for detecting them.
This paper provides a comprehensive overview of anomaly detection in time series data, including different types of anomalies and techniques for detecting them.
Save
Este libro proporciona una base sólida en aprendizaje profundo, cubriendo los conceptos, algoritmos y técnicas utilizados en la detección de anomalías. Es una lectura valiosa para quienes buscan explorar técnicas de detección de anomalías más avanzadas.
Este libro proporciona una introducción práctica a la ciencia de datos, cubriendo los conceptos y algoritmos utilizados en la detección de anomalías. Es una lectura valiosa para quienes buscan una comprensión general de los métodos y técnicas de detección de anomalías.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/z1icff/descubriendo
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Effort
1 hora
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Nestor Nicolas Campos Rojas
Language
Español
Good to know
Desarrolla habilidades en detección de anomalías e integración con Power BI
Enseña un servicio cognitivo simple pero potente de Azure: Anomaly Detector
Requiere conocimientos previos en Power BI y lenguaje M
Se enfoca en datos temporales, limitando su aplicabilidad a otros tipos de datos
La duración del proyecto es de solo 1 hora, lo que puede ser insuficiente para una comprensión profunda
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