How Google does Machine Learning en EspaƱol
- 4.6
Course Summary
Learn how to use Google's machine learning tools to build and train models that can make predictions and solve real-world problems.Key Learning Points
- Understand the fundamentals of machine learning and how it works
- Learn how to use Google's machine learning tools like TensorFlow and Cloud ML Engine
- Get hands-on experience building and training machine learning models
Related Topics for further study
- Machine Learning Fundamentals
- Google's Machine Learning Tools
- Building and Training Machine Learning Models
- TensorFlow
- Cloud ML Engine
Learning Outcomes
- Understand the basics of machine learning and how to apply it to real-world problems
- Gain hands-on experience with Google's machine learning tools like TensorFlow and Cloud ML Engine
- Build and train your own machine learning models
Prerequisites or good to have knowledge before taking this course
- Basic programming knowledge (Python recommended)
- Familiarity with linear algebra and statistics
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Applied Data Science with Python
- Machine Learning with Python
Related Education Paths
Related Books
Description
ĀæQuĆ© es el aprendizaje automĆ”tico y quĆ© tipos de problemas puede solucionar? Google concibe el aprendizaje automĆ”tico de una forma algo diferente: considera que se trata no solo de datos, sino tambiĆ©n de lĆ³gica. Hablaremos de por quĆ© es Ćŗtil para los cientĆficos de datos concebirlo asĆ cuando piensan en compilar una canalizaciĆ³n de modelos de aprendizaje automĆ”tico.
Outline
- IntroducciĆ³n al curso
- IntroducciĆ³n a la especializaciĆ³n sobre AA en GCP
- ĀæPor quĆ© elegir Google?
- ĀæPor quĆ© elegir Google Cloud?
- Lo Ćŗltimo de Google
- IntroducciĆ³n al AA en Google Cloud
- QuƩ significa tener un enfoque centrado en la IA
- QuƩ significa tener un enfoque centrado en la IA
- Dos etapas del AA
- AA en productos de Google
- AA en Google Fotos
- Google Traductor y Gmail
- CĆ³mo reemplazar reglas heurĆsticas
- Modelos previamente entrenados
- Aprendizaje automƔtico con Sara Robinson (AA, no reglas)
- API de Vision en acciĆ³n
- API de Video Intelligence
- API de Cloud Speech-to-Text
- TraducciĆ³n y NL4
- Text-to-Speech
- DialogFlow
- IntroducciĆ³n al lab: IntroducciĆ³n a las API de AA previamente entrenadas
- SoluciĆ³n del lab: CĆ³mo invocar API de aprendizaje automĆ”tico
- Enfoque centrado en los datos
- Una estrategia de datos
- Desviaciones entre el entrenamiento y la deriva
- Fases de entrenamiento del AA
- IntroducciĆ³n al lab: Enmarcado de un problema de AA
- SĆntesis del lab
- DemostraciĆ³n: AA en aplicaciones
- QuƩ significa tener un enfoque centrado en la IA
- IntroducciĆ³n al enfoque centrado en la IA
- API de AA previamente entrenadas
- Enfoque centrado en los datos
- CĆ³mo utiliza Google el AA
- Una estrategia de AA
- Transforme su empresa
- IntroducciĆ³n
- La sorpresa del AA
- El ingrediente secreto
- El AA y los procesos empresariales
- AnƔlisis detallado del final de las fases
- CĆ³mo utiliza Google el AA
- Transforme su empresa
- CĆ³mo utiliza Google el AA
- AA inclusivo
- Aprendizaje automƔtico y sesgo humano
- CĆ³mo evaluar mĆ©tricas para la inclusiĆ³n
- Mediciones estadĆsticas y compensaciones aceptables
- Igualdad de oportunidades
- CĆ³mo simular decisiones
- CĆ³mo encontrar errores en su conjunto de datos con Facets
- AA inclusivo
- AA inclusivo
- Notebooks de Python en la nube
- IntroducciĆ³n al mĆ³dulo
- AI Platform Notebooks
- DemostraciĆ³n: AI Platform Notebooks
- Proceso de desarrollo
- CƔlculos y almacenamiento
- IntroducciĆ³n al lab: CĆ³mo analizar datos con AI Platform Notebooks y BigQuery
- SĆntesis del lab: CĆ³mo analizar datos con AI Platform Notebooks y BigQuery
- AI Platform Notebooks
- Notebooks de Python en la nube
- Notebooks de Python en la nube
- Resumen
- Resumen del curso
Summary of User Reviews
Discover the power of Google Machine Learning with Coursera. This course has received rave reviews from students who have found it to be an engaging, informative and practical introduction to machine learning. Many users have praised the course for its comprehensive curriculum that is easy to follow and understand.Key Aspect Users Liked About This Course
The course curriculum is comprehensive and easy to followPros from User Reviews
- Easy to understand and well-explained concepts
- Practical exercises and assignments for hands-on learning
- Great pace and structure
- Excellent instructors and support staff
- Real-world examples and case studies
Cons from User Reviews
- Some technical issues with the platform
- The course may be too basic for advanced learners
- Some assignments are too difficult for beginners
- Not enough focus on certain topics
- Limited opportunities for interaction with other learners