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Nestor Nicolas Campos Rojas

En este proyecto de 1 hora, aprenderás a desarrollar un modelo de Machine Learning usando ML.NET.

Además, aprenderás a simplificar la creación inicial de aplicaciones y modelos usando ML.NET Model Builder.

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What's inside

Syllabus

Haciendo modelos con ML.NET
Al final de este proyecto, tú podrías crear e integrar tus propios modelos de Machine Learning en aplicaciones construidas con C#, a partir de la librería ML.NET

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Develops hands-on skills in using and integrating Machine Learning models in C# applications using ML.NET's built-in tools
Strengthens learners' knowledge of Machine Learning concepts and practices within the context of C# development
Suitable for learners with foundational knowledge in C# programming and an interest in incorporating Machine Learning into their C# projects

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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 Haciendo modelos con ML.NET with these activities:
Revisa conceptos básicos de programación antes de comenzar el curso
Fortalece tu base de programación revisando conceptos esenciales antes de comenzar el curso de ML.NET.
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  • Repasa los conceptos básicos de programación, como variables, tipos de datos y estructuras de control.
  • Practica la escritura de código simple en C# u otro lenguaje de programación orientado a objetos.
Asiste a talleres sobre Machine Learning y ML.NET
Amplía tus conocimientos y habilidades asistiendo a talleres impartidos por expertos en Machine Learning y ML.NET.
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  • Busca talleres relevantes sobre ML.NET y Machine Learning.
  • Regístrate y asiste a los talleres.
  • Toma notas y participa activamente en las discusiones.
Sigue tutoriales para mejorar tus habilidades
Expande tus conocimientos y habilidades siguiendo tutoriales en línea sobre Machine Learning y ML.NET.
Browse courses on Machine Learning
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  • Busca tutoriales de calidad sobre ML.NET y modelos de Machine Learning.
  • Completa los tutoriales siguiendo cuidadosamente las instrucciones.
  • Pon en práctica los conceptos y las técnicas aprendidas en los tutoriales.
Three other activities
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Practica ejercicios sobre modelos ML.NET
Fortalece tu comprensión de los modelos ML.NET resolviendo ejercicios y problemas de práctica.
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  • Encuentra conjuntos de datos y ejercicios de práctica relevantes para modelos ML.NET.
  • Resuelve los ejercicios siguiendo un enfoque sistemático.
  • Compara tus soluciones con las respuestas correctas para identificar áreas de mejora.
Crea un modelo de Machine Learning simple usando ML.NET
Aplica tus conocimientos prácticos creando un modelo de Machine Learning real utilizando ML.NET.
Browse courses on ML.Net
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  • Define un problema de Machine Learning que desees resolver.
  • Recopila y prepara un conjunto de datos relevante para el problema.
  • Entrena un modelo de Machine Learning utilizando ML.NET.
  • Evalúa el rendimiento de tu modelo y realiza ajustes según sea necesario.
Contribuye a proyectos de código abierto relacionados con ML.NET
Amplía tus habilidades prácticas y apoya el ecosistema de ML.NET contribuyendo a proyectos de código abierto.
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  • Identifica proyectos de código abierto de ML.NET que te interesen.
  • Lee la documentación y familiarízate con el proyecto.
  • Haz cambios, corrige errores o agrega nuevas funciones al proyecto.
  • Envía una solicitud de extracción para revisar y fusionar tus contribuciones.

Career center

Learners who complete Haciendo modelos con ML.NET will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineers use their programming skills to design, build, and implement machine learning algorithms. By taking this course, you can build a foundation of knowledge in machine learning. This will help lead to your success as a Machine Learning Engineer.
Machine Learning Researcher
Machine Learning Researchers use their skills in machine learning, statistics, and programming to research and develop new machine learning algorithms. This course can help you get started in a role as a Machine Learning Researcher by providing you with a foundation in machine learning.
Data Scientist
Data Scientists use their knowledge of machine learning, statistics, and programming to analyze data and extract insights. This course can help you get started in a role as a Data Scientist by providing you with a foundation in machine learning.
Project Manager
Project Managers use their skills in project management, business analysis, and programming to manage projects. This course can help you get started in a role as a Project Manager by providing you with a foundation in machine learning. This can be helpful for managing projects that use machine learning.
Product Manager
Product Managers use their skills in product management, business analysis, and programming to develop and manage products. This course can help you get started in a role as a Product Manager by providing you with a foundation in machine learning. This can be helpful for developing products that use machine learning.
Data Engineer
Data Engineers use their skills in data engineering, data analysis, and programming to design, build, and implement data pipelines. This course can help you get started in a role as a Data Engineer by providing you with a foundation in machine learning. This can be helpful for developing data pipelines that use machine learning techniques.
Quantitative Analyst
Quantitative Analysts use their skills in mathematics, statistics, and programming to analyze data and develop financial models. This course can help you get started in a role as a Quantitative Analyst by providing you with a foundation in machine learning. This can be helpful for developing financial models using machine learning techniques.
Data Analyst
Data Analysts use their skills in data analysis, statistics, and programming to analyze data and extract insights. This course can help you get started in a role as a Data Analyst by providing you with a foundation in machine learning. This can be helpful for analyzing data using machine learning techniques.
Business Analyst
Business Analysts use their skills in business analysis, data analysis, and programming to analyze business processes and develop solutions. This course can help you get started in a role as a Business Analyst by providing you with a foundation in machine learning. This can be helpful for analyzing business processes using machine learning techniques.
Software Engineer
Software Engineers use their programming skills to design, build, and implement software applications. This course can help you get started in a role as a Software Engineer by providing you with a foundation in machine learning. This can be helpful for developing software applications that use machine learning.

Reading list

We've selected ten 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 Haciendo modelos con ML.NET.
Este libro proporciona una base sólida en los fundamentos teóricos del machine learning. Cubre temas como el modelado bayesiano y la optimización.
Este libro es una guía completa para el machine learning con Python. Cubre una amplia gama de temas, desde los conceptos básicos hasta los algoritmos avanzados.
Este libro es una guía completa para el machine learning con big data. Cubre una amplia gama de temas, desde los conceptos básicos hasta los algoritmos avanzados.
Este libro es una guía práctica para el machine learning con Python. Cubre una amplia gama de temas, desde los conceptos básicos hasta los algoritmos avanzados.
Aunque este libro se centra en Python, brinda una base sólida en los principios y algoritmos de aprendizaje automático, lo que es beneficioso para los estudiantes de ML.NET que buscan una comprensión más profunda.

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