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Generando modelos con Auto Machine Learning

Nestor Nicolas Campos Rojas

En este proyecto de 1 hora, aprenderás a desarrollar modelos supervisados utilizando librerías de Auto Machine Learning (TPOT, MLBox y H2O) y optimizar los parámetros para hacer una búsqueda inteligencia de los mejores modelos.

Entenderás cuándo aplicar este tipo de librerías y en cuáles contextos no son viables de utilizar.

Además, podrás analizar los detalles de cada modelo generado, reutilizar los códigos o exportarlos para su posterior uso en entornos productivos.

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What's inside

Syllabus

Generando modelos con Auto Machine Learning

Al final de este proyecto, tú entenderás y aplicarás diversas librerías de AutoML para encontrar el mejor modelo para un conjunto de datos determinado, iterando sobre un conjunto de algoritmos supervisados con las librerías.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces learners to advanced concepts in machine learning, including Auto Machine Learning (AutoML) techniques

Prepares learners to use AutoML libraries to optimize model parameters and find the best models for their datasets

Helps learners understand the limitations of AutoML libraries

Provides hands-on experience with AutoML libraries, including TPOT, MLBox, and H2O

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Reviews summary

Generando modelos con auto machine learning

This course is a practical guide on how to use Auto Machine Learning (AutoML) libraries. Its goal is to show users when to apply these libraries and in what situations they may not be applicable. Students will appreciate the clarity in explaining the trial and training phases, cleaning data, and optimizing parameters.

Sound technical knowledge

"Técnicamente me gusto la claridad en explicar la fase de prueba y entrenamiento, y sobre todo la limpieza de datos, que es una etapa crucial en este tipo de proyectos."

Clear examples

"Espectacular el ejemplo y la claridad de la explicacion!"

Superficial content

"Mucho del curso es paja, comienza con los mismos problemas en todos los videos.Un contenido muy superficial, "

Uncertain instructor knowledge

"Al profesor no proyecta seguridad y conocimiento en su forma de expresarse, da la impresión de no ser experto"

Poor audiovisual quality

"El audio es muy malo, aveces no se entiende lo que dice el profesor.En algunas partes el video se ve mal, tipo estatica."

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 Generando modelos con Auto Machine Learning with these activities:

Refresher on Supervised Machine Learning Models

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Review fundamental concepts of supervised machine learning models to strengthen understanding before starting the course.

Browse courses on Machine Learning Models

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Review types of supervised machine learning models (e.g., linear regression, decision trees, support vector machines).
Recall the process of training and evaluating supervised machine learning models.

Compile Study Materials: Notes and Resources

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Organize notes, assignments, and additional resources to enhance understanding and retention of course content.

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Review and consolidate lecture notes.
Collect and organize assignments, quizzes, and exams.
Gather and review external resources such as articles, tutorials, and videos.

Guided Tutorial: TPOT, MLBox, and H2O for Auto Machine Learning

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Explore tutorials and documentation to gain practical experience using the TPOT, MLBox, and H2O libraries for Auto Machine Learning.

Browse courses on TPOT

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Follow step-by-step tutorials on how to install and use these libraries.
Experiment with different parameters and algorithms to optimize model performance.

Four other activities

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Practice Drills: Optimizing Model Parameters

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Engage in practice drills to develop proficiency in optimizing model parameters for Auto Machine Learning.

Browse courses on Machine Learning Optimization

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Practice using grid search or Bayesian optimization techniques.
Analyze the impact of different parameter settings on model performance.

Attend a Workshop on Auto Machine Learning

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Attend a workshop conducted by experts to gain hands-on experience and insights into Auto Machine Learning.

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Participate in interactive sessions and demonstrations led by industry professionals.
Engage in discussions and Q&A with experts in the field.

Project: Develop and Deploy an Auto Machine Learning Model

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Apply the concepts learned by developing and deploying an Auto Machine Learning model to solve a real-world problem.

Browse courses on Machine Learning Model

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Define the problem statement and gather relevant data.
Apply Auto Machine Learning techniques to select and optimize a model.
Deploy the model and evaluate its performance in a production environment.

Participate in an Auto Machine Learning Competition

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Challenge yourself by participating in an Auto Machine Learning competition to test your skills and learn from others.

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Join a competition and study the provided dataset.
Apply Auto Machine Learning techniques to develop a high-performing model.

Career center

Learners who complete Generando modelos con Auto Machine Learning will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

The "Generando modelos con Auto Machine Learning" course is highly relevant to Machine Learning Engineers, who are responsible for designing, developing, and deploying machine learning models. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and evaluating model performance. This knowledge will help Machine Learning Engineers build and deploy models with greater accuracy and efficiency, which is essential for success in the field.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist would greatly benefit from taking the "Generando modelos con Auto Machine Learning" course. Data Scientists typically develop models using machine learning algorithms to extract knowledge from data and provide insights to stakeholders. The course covers topics such as generating models with AutoML, analyzing the details of each generated model, and exporting the models for production use. This knowledge will help Data Scientists build and deploy models more efficiently and effectively, which is a crucial skill in the field.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers who are interested in developing applications that leverage machine learning may benefit from taking the "Generando modelos con Auto Machine Learning" course. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Software Engineers build and deploy machine learning models efficiently and effectively, which can lead to innovative and successful software products.

See salaries and explore the career path for Software Engineer

Operations Research Analyst

Operations Research Analysts who are interested in using machine learning to optimize business operations may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Operations Research Analysts build and deploy machine learning models efficiently and effectively, which can lead to more efficient and profitable business operations.

See salaries and explore the career path for Operations Research Analyst

Quantitative Analyst

Quantitative Analysts who are interested in developing and deploying machine learning models for financial analysis may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Quantitative Analysts build and deploy machine learning models efficiently and effectively, which can lead to more accurate and profitable financial analysis.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts who are interested in using machine learning to analyze financial data and make investment decisions may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Financial Analysts build and deploy machine learning models efficiently and effectively, which can lead to more accurate and profitable investment decisions.

See salaries and explore the career path for Financial Analyst

Insurance Analyst

Insurance Analysts who are interested in using machine learning to assess and manage insurance risk may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Insurance Analysts build and deploy machine learning models efficiently and effectively, which can lead to more accurate and effective risk assessment and management.

See salaries and explore the career path for Insurance Analyst

Market Research Analyst

Market Research Analysts who are interested in using machine learning to analyze market data and consumer behavior may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, analyzing the details of each generated model, and deploying the models in production. This knowledge will help Market Research Analysts build and deploy machine learning models efficiently and effectively, which can lead to more accurate and insightful market analysis.

See salaries and explore the career path for Market Research Analyst

Data Analyst

Data Analysts may find the "Generando modelos con Auto Machine Learning" course helpful in their work. Data Analysts typically use data analysis techniques to extract insights from data and support decision-making. The course covers topics such as using AutoML libraries to generate models, analyzing the details of each generated model, and exporting the models for production use. This knowledge will help Data Analysts build and deploy models to support their data analysis tasks, which can lead to more accurate and efficient decision-making.

See salaries and explore the career path for Data Analyst

Risk Analyst

Risk Analysts who are interested in using machine learning to assess and manage financial risk may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Risk Analysts build and deploy machine learning models efficiently and effectively, which can lead to more accurate and effective risk assessment and management.

See salaries and explore the career path for Risk Analyst

Cloud Architect

Cloud Architects who are interested in designing and managing cloud architectures that support machine learning may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Cloud Architects design and manage cloud architectures that are efficient, scalable, and able to support the deployment of machine learning models.

See salaries and explore the career path for Cloud Architect

Data Architect

Data Architects who are interested in designing and managing data architectures that support machine learning may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Data Architects design and manage data architectures that are efficient, scalable, and able to support the deployment of machine learning models.

See salaries and explore the career path for Data Architect

Management Consultant

Management Consultants who are interested in using machine learning to solve business problems may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, optimizing model parameters, and deploying models in production. This knowledge will help Management Consultants build and deploy machine learning models efficiently and effectively, which can lead to more innovative and successful business solutions.

See salaries and explore the career path for Management Consultant

Product Manager

Product Managers who are responsible for developing and managing products that leverage machine learning may find the "Generando modelos con Auto Machine Learning" course helpful. The course covers topics such as using AutoML libraries to generate models, analyzing the details of each generated model, and deploying the models in production. This knowledge will help Product Managers understand the capabilities and limitations of machine learning models, which can lead to better decision-making and more successful products.

See salaries and explore the career path for Product Manager

Business Analyst

Business Analysts who are interested in using data analysis to support business decisions may benefit from taking the "Generando modelos con Auto Machine Learning" course. The course covers topics such as using AutoML libraries to generate models, analyzing the details of each generated model, and deploying the models in production. This knowledge will help Business Analysts build and deploy models to support their business analysis tasks, which can lead to more accurate and efficient decision-making.

See salaries and explore the career path for Business Analyst

Reading list

We've selected 14 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 Generando modelos con Auto Machine Learning.

Artificial Intelligence: A Modern Approach, Global...

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This classic textbook provides a comprehensive overview of artificial intelligence, covering its history, foundations, and various subfields. It valuable resource for learners looking to gain a deeper understanding of the principles and applications of AI.

Generando modelos con Auto Machine Learning

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Generando modelos con auto machine learning

Activities

Career center

Reading list

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