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Leire Ahedo
Este proyecto es un curso práctico y efectivo para aprender a como desplegar modelos en Azure. Aprenderemos además a generar modelos de Machine Learning desde cero con Pycaret.
Al acabar este curso abras aprendido el ciclo completo de desarrollo de modelos de Machine Learning con Pycaret y su despliegue en la plataforma de Azure.
Register for this course and see more details by visiting:
OpenCourser.com/course/qibqar/desplegando
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Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches skills and knowledge whose use may be against the law in certain jurisdictions
Requires learners to come in with extensive background knowledge first
Develops professional skills or deep expertise in a particular topic or set of topics
Explores standard industry practices
Gives learners an edge in understanding groundbreaking topics
Covers unique perspectives and ideas that may add color to other topics and subjects
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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 Desplegando modelos de Machine Learning con Pycaret en Azure with these
activities:
Organize your course notes and resources
Show steps
Enhance your learning experience by整理ing and reviewing your course materials regularly.
Show steps
-
Create a system for organizing notes, assignments, and quizzes
-
Review your materials regularly to reinforce your understanding
Review Python
Show steps
Reinforce your knowledge on Python before the course begins, increasing your comfort level and reducing friction.
Browse courses on
Python
Show steps
-
Review basic data types and data structures
-
Practice writing and executing simple Python programs
-
Complete beginner-level Python tutorials
Follow Pycaret tutorials
Show steps
Gain a deeper understanding of Pycaret's capabilities and features through hands-on tutorials.
Browse courses on
Pycaret
Show steps
-
Experiment with different parameters and models
-
Identify tutorials relevant to your learning objectives
-
Follow the tutorials step-by-step and implement the techniques
Five other activities
Expand to see all activities and additional details
Show all eight activities
Watch Azure Machine Learning Service Tutorials
Show steps
Learn about the key features and functionalities of Azure Machine Learning Service.
Browse courses on
Azure Machine Learning Service
Show steps
-
Identify tutorials that cover your areas of interest
-
Follow the tutorials and implement the concepts
-
Experiment with different services and resources
Join a Pycaret study group
Show steps
Connect with fellow learners, share knowledge, and enhance your understanding of Pycaret.
Browse courses on
Pycaret
Show steps
-
Find or create a study group
-
Participate actively in discussions
-
Collaborate on projects
Attend an Azure Machine Learning Service workshop
Show steps
Learn from industry experts, gain hands-on experience, and enhance your understanding of Azure Machine Learning Service.
Browse courses on
Azure Machine Learning Service
Show steps
-
Identify and register for a relevant workshop
-
Attend the workshop and actively participate
-
Engage with instructors and other attendees
Solve Pycaret coding exercises
Show steps
Sharpen your Pycaret skills and problem-solving abilities by working through coding exercises.
Browse courses on
Pycaret
Show steps
-
Find coding exercises online or in the course materials
-
Attempt to solve the exercises independently
-
Review your solutions and identify areas for improvement
Build a portfolio of deployed machine learning projects
Show steps
Demonstrate your skills and gain valuable experience by deploying real-world machine learning projects.
Browse courses on
Machine Learning
Show steps
-
Identify and select suitable projects
-
Design and implement end-to-end machine learning solutions
-
Deploy the projects and evaluate their performance
Organize your course notes and resources
Show steps
Enhance your learning experience by整理ing and reviewing your course materials regularly.
Show steps
Show steps
Show steps
- Create a system for organizing notes, assignments, and quizzes
- Review your materials regularly to reinforce your understanding
Review Python
Show steps
Reinforce your knowledge on Python before the course begins, increasing your comfort level and reducing friction.
Browse courses on
Python
Show steps
Show steps
Show steps
- Review basic data types and data structures
- Practice writing and executing simple Python programs
- Complete beginner-level Python tutorials
Follow Pycaret tutorials
Show steps
Gain a deeper understanding of Pycaret's capabilities and features through hands-on tutorials.
Browse courses on
Pycaret
Show steps
Show steps
Show steps
- Experiment with different parameters and models
- Identify tutorials relevant to your learning objectives
- Follow the tutorials step-by-step and implement the techniques
Five other activities
Expand to see all activities and additional details
Show all eight activities
Watch Azure Machine Learning Service Tutorials
Show steps
Learn about the key features and functionalities of Azure Machine Learning Service.
Browse courses on
Azure Machine Learning Service
Show steps
Show steps
Show steps
- Identify tutorials that cover your areas of interest
- Follow the tutorials and implement the concepts
- Experiment with different services and resources
Join a Pycaret study group
Show steps
Connect with fellow learners, share knowledge, and enhance your understanding of Pycaret.
Browse courses on
Pycaret
Show steps
Show steps
Show steps
- Find or create a study group
- Participate actively in discussions
- Collaborate on projects
Attend an Azure Machine Learning Service workshop
Show steps
Learn from industry experts, gain hands-on experience, and enhance your understanding of Azure Machine Learning Service.
Browse courses on
Azure Machine Learning Service
Show steps
Show steps
Show steps
- Identify and register for a relevant workshop
- Attend the workshop and actively participate
- Engage with instructors and other attendees
Solve Pycaret coding exercises
Show steps
Sharpen your Pycaret skills and problem-solving abilities by working through coding exercises.
Browse courses on
Pycaret
Show steps
Show steps
Show steps
- Find coding exercises online or in the course materials
- Attempt to solve the exercises independently
- Review your solutions and identify areas for improvement
Build a portfolio of deployed machine learning projects
Show steps
Demonstrate your skills and gain valuable experience by deploying real-world machine learning projects.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify and select suitable projects
- Design and implement end-to-end machine learning solutions
- Deploy the projects and evaluate their performance
Career center
Learners who complete Desplegando modelos de Machine Learning con Pycaret en Azure will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers integrate expertise in statistics, software development, and engineering to design, develop, deploy, and maintain machine learning systems. They may be involved in the full lifecycle of a machine learning project, from data collection and preparation to model training and deployment. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills are essential for Machine Learning Engineers who need to be able to deploy and maintain machine learning models in a production environment.
Data Scientist
Data Scientist
Data Scientists use a combination of statistics, computer science, and business knowledge to extract valuable insights from data. They may also design and implement machine learning models and algorithms as part of their work. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills are helpful for Data Scientists who need to be able to deploy and maintain machine learning models in a production environment.
Software Engineer
Software Engineer
Software Engineers design, develop, implement, and maintain software systems. They may work on a variety of projects, including web applications, mobile applications, and enterprise software. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Software Engineers who are working on projects that involve machine learning.
Cloud Architect
Cloud Architect
Cloud Architects design, build, and manage cloud computing systems. They may work on a variety of projects, including designing cloud infrastructure, migrating applications to the cloud, and developing cloud-native applications. This course teaches you how to deploy machine learning models on Azure, which is one of the leading cloud computing platforms. These skills may be helpful for Cloud Architects who are working on projects that involve machine learning.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. They may work on a variety of projects, including analyzing customer data, identifying trends, and forecasting future outcomes. This course teaches you how to generate machine learning models from scratch with Pycaret. These skills may be helpful for Data Analysts who are working on projects that involve machine learning.
Business Analyst
Business Analyst
Business Analysts use data and analytics to understand business needs and develop solutions. They may work on a variety of projects, including developing business plans, analyzing financial data, and identifying opportunities for growth. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Business Analysts who are working on projects that involve machine learning.
Product Manager
Product Manager
Product Managers are responsible for the development and lifecycle of a product. They may work on a variety of projects, including defining product requirements, managing product development, and launching new products. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Product Managers who are working on products that involve machine learning.
Project Manager
Project Manager
Project Managers are responsible for planning, executing, and completing projects. They may work on a variety of projects, including developing new products, launching new businesses, and implementing new processes. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Project Managers who are working on projects that involve machine learning.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation for a variety of products and services. They may work on a variety of projects, including writing user manuals, developing online help systems, and creating marketing materials. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Technical Writers who are working on projects that involve machine learning.
Sales Engineer
Sales Engineer
Sales Engineers work with customers to understand their needs and recommend solutions. They may also be responsible for demonstrating products, providing technical support, and closing deals. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Sales Engineers who are working on projects that involve machine learning.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. They may work on a variety of projects, including developing marketing plans, managing marketing budgets, and evaluating marketing results. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills may be helpful for Marketing Managers who are working on campaigns that involve machine learning.
Human Resources Manager
Human Resources Manager
Human Resources Managers are responsible for managing the human resources function of an organization. They may work on a variety of projects, including recruiting and hiring employees, developing training programs, and managing employee benefits. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills are unlikely to be directly helpful for Human Resources Managers, but they may be helpful for HR professionals who are working on projects that involve machine learning.
Operations Manager
Operations Manager
Operations Managers are responsible for managing the operations of an organization. They may work on a variety of projects, including developing operational plans, managing budgets, and ensuring compliance with regulations. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills are unlikely to be directly helpful for Operations Managers, but they may be helpful for operations professionals who are working on projects that involve machine learning.
Financial Analyst
Financial Analyst
Financial Analysts use financial data to make investment decisions. They may work on a variety of projects, including analyzing financial statements, developing financial models, and making investment recommendations. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills are unlikely to be directly helpful for Financial Analysts, but they may be helpful for financial professionals who are working on projects that involve machine learning.
Customer Service Manager
Customer Service Manager
Customer Service Managers are responsible for managing the customer service function of an organization. They may work on a variety of projects, including developing customer service policies, training customer service representatives, and managing customer feedback. This course teaches you how to deploy machine learning models on Azure and generate models from scratch with Pycaret. These skills are unlikely to be directly helpful for Customer Service Managers, but they may be helpful for customer service professionals who are working on projects that involve machine learning.
For more career information including salaries, visit:
OpenCourser.com/course/qibqar/desplegando
Reading list
We've selected 15 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
Desplegando modelos de Machine Learning con Pycaret en Azure.
Save
Covers a wide range of predictive modeling techniques, including linear regression, logistic regression, and decision trees. Provides a practical guide to building and evaluating predictive models.
Provides a comprehensive guide to using Keras for machine learning tasks. It covers topics such as data preparation, model training, and model deployment.
Provides a comprehensive guide to using Python for deep learning tasks. It covers topics such as data preparation, model training, and model evaluation.
Provides a comprehensive guide to using Python for natural language processing tasks. It covers topics such as data preparation, model training, and model evaluation.
Provides a comprehensive guide to speech and language processing. It covers topics such as phonetics, phonology, morphology, syntax, semantics, and pragmatics.
A comprehensive guide to machine learning with Python, covering a wide range of topics from data preprocessing to model evaluation. Offers a deep dive into the technical aspects of machine learning.
Provides a practical introduction to machine learning for predictive data analytics. Covers a wide range of machine learning algorithms and techniques.
Covers a wide range of statistical learning topics, including supervised learning, unsupervised learning, and model selection. Provides a comprehensive overview of the field of statistical learning.
Covers advanced machine learning techniques using TensorFlow 2 and Keras. Provides a deeper understanding of the technical implementation of machine learning algorithms.
Provides a theoretical perspective on machine learning, focusing on Bayesian inference and optimization. Offers a deeper understanding of the underlying mathematical foundations of machine learning.
Covers the mathematical foundations of machine learning, including linear algebra, calculus, and probability theory. Provides a deeper understanding of the mathematical concepts underlying machine learning algorithms.
Focuses on statistical learning with sparsity, covering topics such as the lasso and other regularization techniques. Provides a deeper understanding of the statistical aspects of machine learning.
Covers a wide range of machine learning topics, including supervised learning, unsupervised learning, and Bayesian inference. Provides a comprehensive overview of the field of machine learning.
Focuses on deep learning, a subfield of machine learning concerned with artificial neural networks. Provides additional depth on the theoretical and practical aspects of deep learning.
Provides a collection of recipes for common machine learning tasks in Python. It covers topics such as data preparation, model training, and model evaluation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qibqar/desplegando
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Leire Ahedo
Good to know
Teaches skills and knowledge whose use may be against the law in certain jurisdictions
Requires learners to come in with extensive background knowledge first
Develops professional skills or deep expertise in a particular topic or set of topics
Explores standard industry practices
Gives learners an edge in understanding groundbreaking topics
Covers unique perspectives and ideas that may add color to other topics and subjects
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