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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender Deep Learning con ejercicios aplicados. Aprenderás desde cero los fundamentos del Deep Learning. Después irás aprendiendo a desarrollar redes neuronales con Python y Keras a través de ejercicios prácticos.
Gracias a este curso aprenderás a programar tus propios modelos de Deep Learning. Gracias a esto podrás predecir si un cliente comprará o no un producto, el precio de la vivienda, etc.
Register for this course and see more details by visiting:
OpenCourser.com/course/nzadsz/curso
What's inside
Syllabus
Inteligencia Artificial en Power BI
En este curso se aprenderá a programar redes neuronales con Keras
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Curso multi-modal que usa videos, lecturas y debates
Fortalece los conocimientos fundamentales para principiantes
Se centra en las bases del Deep Learning
Requiere conocimientos previos
Se necesita contar con una computadora y acceso a Internet
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Save Curso Completo de Deep Learning to your list so you can find it easily later:
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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 Curso Completo de Deep Learning with these
activities:
Complete Python Tutorial
Show steps
Completing a Python tutorial will brush up on your Python skills and prepare you for the more advanced concepts covered in this course.
Browse courses on
Python
Show steps
-
Go to the Python tutorial website.
-
Follow the tutorial steps.
-
Complete the practice exercises.
Follow Keras Tutorial
Show steps
Following a Keras tutorial will introduce you to the basics of Keras and how to use it for deep learning.
Browse courses on
Keras
Show steps
-
Go to the Keras tutorial website.
-
Follow the tutorial steps.
-
Complete the practice exercises.
Develop a Deep Learning Model for a Real-World Problem
Show steps
Developing a deep learning model for a real-world problem will allow you to apply the concepts covered in this course to a practical scenario.
Show steps
-
Identify a problem that can be solved with deep learning.
-
Gather data for your project.
-
Build a deep learning model.
-
Train and evaluate your model.
-
Deploy your model.
Show all three activities
Complete Python Tutorial
Show steps
Completing a Python tutorial will brush up on your Python skills and prepare you for the more advanced concepts covered in this course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Go to the Python tutorial website.
- Follow the tutorial steps.
- Complete the practice exercises.
Follow Keras Tutorial
Show steps
Following a Keras tutorial will introduce you to the basics of Keras and how to use it for deep learning.
Browse courses on
Keras
Show steps
Show steps
Show steps
- Go to the Keras tutorial website.
- Follow the tutorial steps.
- Complete the practice exercises.
Develop a Deep Learning Model for a Real-World Problem
Show steps
Developing a deep learning model for a real-world problem will allow you to apply the concepts covered in this course to a practical scenario.
Show steps
Show steps
Show steps
- Identify a problem that can be solved with deep learning.
- Gather data for your project.
- Build a deep learning model.
- Train and evaluate your model.
- Deploy your model.
Show all three activities
Career center
Learners who complete Curso Completo de Deep Learning will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They use their knowledge of machine learning algorithms, data analysis, and software engineering to develop solutions to complex problems. This course would be a valuable asset to an aspiring Machine Learning Engineer, as it would provide them with a strong foundation in deep learning, one of the most important subfields of machine learning.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers help build and maintain artificial intelligence systems. They use their knowledge of machine learning, deep learning, and other AI techniques to develop solutions to complex problems. This course would be a valuable asset to an aspiring Artificial Intelligence Engineer, as it would provide them with a strong foundation in deep learning, one of the most important subfields of AI.
Data Scientist
Data Scientist
Data Scientists use their knowledge of statistics, machine learning, and other data analysis techniques to extract insights from data. This course would be helpful to an aspiring Data Scientist, as it would provide them with a strong foundation in deep learning, a valuable tool for data analysis.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines. They use their knowledge of data engineering tools, data analysis techniques, and software engineering to build solutions to complex problems. This course may be helpful to an aspiring Data Engineer, as it would provide them with a strong foundation in deep learning, a valuable tool for data engineering.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics, statistics, and computer science to analyze complex problems and make decisions. This course may be helpful to an aspiring Operations Research Analyst, as it would provide them with a strong foundation in deep learning, a valuable tool for operations research.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. They use their knowledge of programming languages, software design principles, and software engineering tools to build solutions to complex problems. This course may be helpful to an aspiring Software Engineer, as it would provide them with a strong foundation in deep learning, a valuable tool for software development.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their knowledge of mathematics, statistics, and computer science to analyze financial data and make investment decisions. This course may be helpful to an aspiring Quantitative Analyst, as it would provide them with a strong foundation in deep learning, a valuable tool for financial analysis.
Actuary
Actuary
Actuaries use their knowledge of mathematics, statistics, and finance to assess risk and make decisions about insurance and other financial products. This course may be helpful to an aspiring Actuary, as it would provide them with a strong foundation in deep learning, a valuable tool for actuarial science.
Risk Manager
Risk Manager
Risk Managers use their knowledge of risk management, finance, and insurance to identify and manage risks to an organization. This course may be helpful to an aspiring Risk Manager, as it would provide them with a strong foundation in deep learning, a valuable tool for risk management.
Epidemiologist
Epidemiologist
Epidemiologists use their knowledge of epidemiology, statistics, and public health to investigate the causes of disease and develop strategies to prevent and control it. This course may be helpful to an aspiring Epidemiologist, as it would provide them with a strong foundation in deep learning, a valuable tool for epidemiology.
Biostatistician
Biostatistician
Biostatisticians use their knowledge of statistics, mathematics, and biology to analyze biological data. This course may be helpful to an aspiring Biostatistician, as it would provide them with a strong foundation in deep learning, a valuable tool for biostatistics.
Insurance Analyst
Insurance Analyst
Insurance Analysts use their knowledge of insurance, finance, and mathematics to analyze insurance data and make decisions about insurance products. This course may be helpful to an aspiring Insurance Analyst, as it would provide them with a strong foundation in deep learning, a valuable tool for insurance analysis.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of finance, accounting, and economics to analyze financial data and make investment decisions. This course may be helpful to an aspiring Financial Analyst, as it would provide them with a strong foundation in deep learning, a valuable tool for financial analysis.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business processes, data analysis, and software engineering to identify and solve business problems. This course may be helpful to an aspiring Business Analyst, as it would provide them with a strong foundation in deep learning, a valuable tool for business analysis.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. They use their knowledge of market research, product design, and business strategy to create products that meet the needs of customers. This course may be helpful to an aspiring Product Manager, as it would provide them with a strong foundation in deep learning, a valuable tool for product development.
For more career information including salaries, visit:
OpenCourser.com/course/nzadsz/curso
Reading list
We've selected 11 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
Curso Completo de Deep Learning.
Save
Este libro es un recurso completo sobre Deep Learning. Cubre los aspectos teóricos y prácticos del Deep Learning, y proporciona una base sólida para comprender y aplicar técnicas de Deep Learning.
Este libro proporciona una introducción completa a Deep Learning con Python y Keras. Cubre los conceptos fundamentales de Deep Learning, así como técnicas prácticas para desarrollar e implementar modelos de Deep Learning.
Este libro proporciona una introducción práctica al aprendizaje profundo con Fastai y PyTorch. Cubre el desarrollo y la implementación de modelos de aprendizaje profundo.
Este libro ofrece una introducción al procesamiento del lenguaje natural con Deep Learning. Cubre técnicas avanzadas para el modelado del lenguaje y el procesamiento de texto.
Este libro proporciona una introducción al aprendizaje por refuerzo. Cubre los conceptos fundamentales del aprendizaje por refuerzo y ofrece una visión general de las técnicas de aprendizaje por refuerzo.
Save
Este libro proporciona una introducción a la visión por computador. Cubre los algoritmos y técnicas fundamentales utilizados en la visión por computador, incluida la visión artificial.
Este libro ofrece una introducción a los modelos gráficos probabilísticos, que son una poderosa herramienta para representar y razonar sobre la incertidumbre. Es un recurso valioso para comprender los fundamentos teóricos del Deep Learning.
Este libro ofrece una introducción a los métodos de aprendizaje automático para datos dispersos. Cubre técnicas como la selección de características y la regularización.
Este libro proporciona una introducción a las matemáticas utilizadas en el aprendizaje automático. Cubre conceptos matemáticos fundamentales, como álgebra lineal, cálculo y probabilidad.
Este libro ofrece una introducción al procesamiento del habla y el lenguaje. Cubre los fundamentos del procesamiento del habla y el lenguaje, así como técnicas avanzadas para el reconocimiento y la síntesis del habla.
Este libro proporciona una introducción al razonamiento bayesiano y al aprendizaje automático bayesiano. Es un recurso útil para comprender los fundamentos teóricos del Deep Learning y cómo se pueden aplicar en la práctica.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/nzadsz/curso
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Effort
2 horas
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Language
Español
Good to know
Curso multi-modal que usa videos, lecturas y debates
Fortalece los conocimientos fundamentales para principiantes
Se centra en las bases del Deep Learning
Requiere conocimientos previos
Se necesita contar con una computadora y acceso a Internet
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