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Google Cloud Training
Quer saber mais sobre o Feature Store da Vertex AI, como melhorar a acurácia dos seus modelos de machine learning e quais colunas de dados contêm os atributos mais úteis? No curso "Feature Engineering", falamos sobre atributos bons e ruins, além de mostrar como fazer o pré-processamento e a transformação deles para otimizar seus modelos. Esse curso tem conteúdo teórico e prático sobre a engenharia de atributos usando o BigQuery ML, Keras e TensorFlow.
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What's inside
Syllabus
Introdução ao curso
Neste módulo, apresentamos uma visão geral do curso e dos objetivos a serem alcançados.
Introdução ao Feature Store da Vertex AI
Read more
Syllabus
Introdução ao curso
Neste módulo, apresentamos uma visão geral do curso e dos objetivos a serem alcançados.
Introdução ao Feature Store da Vertex AI
Read more
Este módulo apresenta o Feature Store da Vertex AI.
De dados brutos a atributos
A engenharia de atributos costuma ser a fase mais demorada e difícil da criação dos projetos de ML. Esse processo começa pelos dados brutos, e você usa seu próprio conhecimento sobre domínios para criar atributos que vão fazer seus algoritmos de machine learning funcionarem. Neste módulo, vamos conferir o que caracteriza um bom atributo e como fazer a representação deles no seu modelo.
Engenharia de atributos
Neste módulo, analisamos as diferenças entre o machine learning e as estatísticas, além de mostrar como executar a engenharia de atributos no BigQuery ML e no Keras. Também vamos abordar algumas práticas avançadas desse processo.
Pré-processamento e criação de atributos
Neste módulo, apresentamos informações sobre o Dataflow, uma tecnologia complementar do Apache Beam. Ambos podem ajudar você a criar e executar o pré-processamento e a engenharia de atributos.
Cruzamentos de atributos – TensorFlow Playground
Os cruzamentos de atributos não têm um papel muito significativo nos processos tradicionais de machine learning. Porém, para os métodos de ML atuais, esses tipos de recursos são parte essencial do seu kit de ferramentas. Neste módulo, você vai aprender a reconhecer os tipos de problemas em que os cruzamentos de atributos desempenham um papel importante no machine learning.
Introdução ao TensorFlow Transform
O TensorFlow Transform (tf.Transform) é uma biblioteca de pré-processamento de dados com o TensorFlow. O tf.Transform é útil para os pré-processamentos que exigem uma passagem completa dos dados, como:
• normalizar um valor de entrada por média e stdev;
• transformar strings em números inteiros ao gerar um vocabulário com a verificação de todos os exemplos de entrada dos valores;
• separar as entradas em buckets com base na distribuição de dados que foi observada.
Neste módulo vamos apresentar os casos de uso do tf.Transform.
Resumo
Este módulo é um resumo do curso Feature Engineering
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Ensina engenharia de atributos para melhorar a precisão de modelos de aprendizado de máquina
Noções básicas e práticas sobre engenharia de atributos usando BigQuery ML, Keras e TensorFlow
Desenvolvido pelo Google Cloud Training, referências reconhecidas na área
Aborda cruzamentos de atributos, relevantes para métodos de aprendizado de máquina atuais
Introdução ao TensorFlow Transform para pré-processamento de dados
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Reviews summary
Feature engineering has technical issues
The course is generally well received. However, learners have expressed technical issues with running the notebooks provided. This may indicate that the course has some issues that may need to be addressed.
The course has technical issues with notebooks
"Os notebooks não funcionam"
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 Feature Engineering em Português Brasileiro with these
activities:
Review core concepts in machine learning and statistics
Show steps
Strengthen your understanding of the underlying concepts in machine learning and statistics to better grasp the principles and practices of feature engineering.
Browse courses on
Machine Learning
Show steps
-
Review textbooks or online resources on machine learning and statistics.
-
Complete practice problems and exercises to test your comprehension.
Review SQL basics
Show steps
Review SQL basic syntax and core concepts to reinforce fundamentals and prepare for course content on feature store manipulation.
Browse courses on
SQL
Show steps
-
Go through an online SQL tutorial or refresher course.
-
Practice writing basic SQL queries using an online SQL editor or database management system.
Explore Google Cloud Platform (GCP) resources for feature engineering
Show steps
Familiarize yourself with GCP services and tools specifically designed for feature engineering, enhancing your understanding of the course content.
Browse courses on
Machine Learning
Show steps
-
Visit the GCP Feature Store documentation and explore its capabilities.
-
Follow a guided tutorial on using BigQuery ML or Keras for feature engineering.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Join a study group or online forum for feature engineering
Show steps
Engage with peers and professionals in the field to exchange knowledge, troubleshoot issues, and gain diverse perspectives on feature engineering.
Browse courses on
Machine Learning
Show steps
-
Search for feature engineering study groups or online forums.
-
Connect with other participants, ask questions, and share your experiences.
BigQuery ML feature engineering project
Show steps
Deepen your understanding of the practical applications of feature engineering by undertaking a hands-on project using BigQuery ML.
Browse courses on
BigQuery ML
Show steps
-
Identify a suitable dataset for your project
-
Use BigQuery ML to create features from the dataset
-
Train a machine learning model using the engineered features
-
Evaluate the performance of your model
Siga tutoriais sobre engenharia de recursos avançada
Show steps
Os tutoriais guiados podem ajudá-lo a aprofundar sua compreensão de técnicas avançadas de engenharia de recursos e aprimorar suas habilidades práticas.
Browse courses on
TensorFlow Transform
Show steps
-
Identifique os recursos relevantes para o seu problema de ML.
-
Aprenda sobre técnicas avançadas de engenharia de recursos, como cruzamentos e transformações não lineares.
-
Aplique TensorFlow Transform para implementar esses recursos em seus modelos de ML.
Work through practice exercises on feature selection and transformation
Show steps
Reinforce your understanding of feature engineering techniques by completing practical exercises that involve feature selection, transformation, and optimization.
Browse courses on
Machine Learning
Show steps
-
Find online resources or textbooks with feature engineering practice problems.
-
Solve these problems, experimenting with different approaches and evaluating the results.
Guided TensorFlow Transform tutorial
Show steps
Reinforce your understanding of the concepts covered in the TensorFlow Transform module by completing the guided tutorial provided by Google.
Show steps
-
Access the TensorFlow Transform tutorial
-
Follow the step-by-step instructions in the tutorial
-
Implement TensorFlow Transform in your code
Develop a project to apply feature engineering techniques
Show steps
Gain hands-on experience by applying feature engineering techniques to a real-world problem, deepening your understanding and solidifying your skills.
Browse courses on
Machine Learning
Show steps
-
Identify a problem or dataset that requires feature engineering.
-
Apply feature selection, transformation, and optimization techniques to the dataset.
-
Evaluate the performance of your model with and without feature engineering.
kaggle competition
Show steps
Challenge yourself by participating in a Kaggle competition that focuses on feature engineering. This will provide you with实战experience that can enhance your practical skills.
Browse courses on
Data Science
Show steps
-
Identify a Kaggle competition that aligns with your interests
-
Familiarize yourself with the competition data and evaluation metrics
-
Apply feature engineering techniques to improve the performance of your model
-
Submit your results to the competition and analyze your performance
Write a blog post or article on a specific feature engineering technique
Show steps
Consolidate your knowledge and enhance your understanding by explaining a particular feature engineering technique to others, clarifying concepts and promoting retention.
Browse courses on
Machine Learning
Show steps
-
Choose a specific feature engineering technique to focus on.
-
Research and gather information about the technique.
-
Write a clear and informative blog post or article.
Contribute to open-source projects related to feature engineering
Show steps
Engage with the broader developer community by contributing to open-source projects that involve feature engineering, fostering collaboration and deepening your understanding.
Browse courses on
Machine Learning
Show steps
-
Identify open-source projects that focus on feature engineering.
-
Contribute code, documentation, or issue reports to these projects.
Review core concepts in machine learning and statistics
Show steps
Strengthen your understanding of the underlying concepts in machine learning and statistics to better grasp the principles and practices of feature engineering.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Review textbooks or online resources on machine learning and statistics.
- Complete practice problems and exercises to test your comprehension.
Review SQL basics
Show steps
Review SQL basic syntax and core concepts to reinforce fundamentals and prepare for course content on feature store manipulation.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Go through an online SQL tutorial or refresher course.
- Practice writing basic SQL queries using an online SQL editor or database management system.
Explore Google Cloud Platform (GCP) resources for feature engineering
Show steps
Familiarize yourself with GCP services and tools specifically designed for feature engineering, enhancing your understanding of the course content.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Visit the GCP Feature Store documentation and explore its capabilities.
- Follow a guided tutorial on using BigQuery ML or Keras for feature engineering.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Join a study group or online forum for feature engineering
Show steps
Engage with peers and professionals in the field to exchange knowledge, troubleshoot issues, and gain diverse perspectives on feature engineering.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Search for feature engineering study groups or online forums.
- Connect with other participants, ask questions, and share your experiences.
BigQuery ML feature engineering project
Show steps
Deepen your understanding of the practical applications of feature engineering by undertaking a hands-on project using BigQuery ML.
Browse courses on
BigQuery ML
Show steps
Show steps
Show steps
- Identify a suitable dataset for your project
- Use BigQuery ML to create features from the dataset
- Train a machine learning model using the engineered features
- Evaluate the performance of your model
Siga tutoriais sobre engenharia de recursos avançada
Show steps
Os tutoriais guiados podem ajudá-lo a aprofundar sua compreensão de técnicas avançadas de engenharia de recursos e aprimorar suas habilidades práticas.
Browse courses on
TensorFlow Transform
Show steps
Show steps
Show steps
- Identifique os recursos relevantes para o seu problema de ML.
- Aprenda sobre técnicas avançadas de engenharia de recursos, como cruzamentos e transformações não lineares.
- Aplique TensorFlow Transform para implementar esses recursos em seus modelos de ML.
Work through practice exercises on feature selection and transformation
Show steps
Reinforce your understanding of feature engineering techniques by completing practical exercises that involve feature selection, transformation, and optimization.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find online resources or textbooks with feature engineering practice problems.
- Solve these problems, experimenting with different approaches and evaluating the results.
Guided TensorFlow Transform tutorial
Show steps
Reinforce your understanding of the concepts covered in the TensorFlow Transform module by completing the guided tutorial provided by Google.
Show steps
Show steps
Show steps
- Access the TensorFlow Transform tutorial
- Follow the step-by-step instructions in the tutorial
- Implement TensorFlow Transform in your code
Develop a project to apply feature engineering techniques
Show steps
Gain hands-on experience by applying feature engineering techniques to a real-world problem, deepening your understanding and solidifying your skills.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify a problem or dataset that requires feature engineering.
- Apply feature selection, transformation, and optimization techniques to the dataset.
- Evaluate the performance of your model with and without feature engineering.
kaggle competition
Show steps
Challenge yourself by participating in a Kaggle competition that focuses on feature engineering. This will provide you with实战experience that can enhance your practical skills.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Identify a Kaggle competition that aligns with your interests
- Familiarize yourself with the competition data and evaluation metrics
- Apply feature engineering techniques to improve the performance of your model
- Submit your results to the competition and analyze your performance
Write a blog post or article on a specific feature engineering technique
Show steps
Consolidate your knowledge and enhance your understanding by explaining a particular feature engineering technique to others, clarifying concepts and promoting retention.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Choose a specific feature engineering technique to focus on.
- Research and gather information about the technique.
- Write a clear and informative blog post or article.
Contribute to open-source projects related to feature engineering
Show steps
Engage with the broader developer community by contributing to open-source projects that involve feature engineering, fostering collaboration and deepening your understanding.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify open-source projects that focus on feature engineering.
- Contribute code, documentation, or issue reports to these projects.
Career center
Learners who complete Feature Engineering em Português Brasileiro will develop knowledge and skills
that may be useful to these careers:
Business Intelligence Analyst
Business Intelligence Analyst
A Business Intelligence Analyst is responsible for gathering, analyzing, and presenting data to help businesses make informed decisions. This course, Feature Engineering em Português Brasileiro, is highly relevant to aspiring Business Intelligence Analysts as it covers data preprocessing and transformation, which are important techniques for extracting valuable insights from large datasets.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for developing, deploying, and maintaining machine learning models. This course, Feature Engineering em Português Brasileiro, is a valuable resource for aspiring Machine Learning Engineers as it covers topics such as data preprocessing, attribute engineering, and feature transformations. These concepts are essential for building and deploying robust machine learning models.
Data Analyst
Data Analyst
A Data Analyst is responsible for analyzing and interpreting data to identify trends and patterns. This course, Feature Engineering em Português Brasileiro, provides a solid foundation for aspiring Data Analysts as it covers topics such as data preprocessing and transformation, which are essential for effective data analysis.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst is responsible for using mathematical and analytical techniques to solve business problems. This course, Feature Engineering em Português Brasileiro, may be useful for those considering a career as an Operations Research Analyst as it provides a foundation in data preprocessing and transformation, which are important skills for solving complex business problems.
Data Scientist
Data Scientist
A Data Scientist is responsible for collecting, cleaning, and analyzing large datasets to extract meaningful insights. This course, Feature Engineering em Português Brasileiro, may be useful to those interested in advancing their career as a Data Scientist. The course covers topics such as attribute representation and attribute engineering, which are fundamental to extracting valuable insights from complex datasets.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst is responsible for developing and implementing mathematical and statistical models to analyze financial data. This course, Feature Engineering em Português Brasileiro, may be useful for those pursuing a career as a Quantitative Analyst as it provides insights into data preprocessing and transformation, which are essential for building and deploying robust financial models.
Financial Analyst
Financial Analyst
A Financial Analyst is responsible for analyzing and interpreting financial data to make investment recommendations. This course, Feature Engineering em Português Brasileiro, may be useful for those interested in becoming Financial Analysts as it introduces data preprocessing and transformation, which play a vital role in extracting meaningful insights from financial data.
Data Architect
Data Architect
A Data Architect is responsible for designing and managing data systems to meet the needs of an organization. This course, Feature Engineering em Português Brasileiro, may be useful for those seeking a career as a Data Architect as it provides insights into data preprocessing and transformation, which are crucial for designing efficient and scalable data systems.
Risk Analyst
Risk Analyst
A Risk Analyst is responsible for identifying and assessing risks to an organization. This course, Feature Engineering em Português Brasileiro, may be useful for those seeking a career as a Risk Analyst as it provides knowledge in data preprocessing and transformation, which are crucial techniques for analyzing and managing risks.
Product Manager
Product Manager
A Product Manager is responsible for planning, developing, and launching products. This course, Feature Engineering em Português Brasileiro, may be useful for those aspiring to become Product Managers as it covers topics such as data preprocessing and transformation, which are valuable techniques for understanding customer needs and developing successful products.
Database Administrator
Database Administrator
A Database Administrator is responsible for designing, maintaining, and optimizing databases. This course, Feature Engineering em Português Brasileiro, may be useful for aspiring Database Administrators as it covers topics such as data preprocessing and transformation, which are essential for ensuring the integrity and efficiency of databases.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and data to identify areas for improvement and drive decision-making. This course, Feature Engineering em Português Brasileiro, may be useful for those looking to enter the field of Business Analysis as it covers topics such as data preprocessing and transformation, which are essential for understanding and improving business processes.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software systems. This course, Feature Engineering em Português Brasileiro, may be useful for those interested in becoming Software Engineers as it covers topics such as data preprocessing and transformation, which are commonly used in software development to improve the efficiency and performance of software systems.
Statistician
Statistician
A Statistician is responsible for collecting, analyzing, interpreting, and presenting data. This course, Feature Engineering em Português Brasileiro, may be useful for those pursuing a career as a Statistician as it covers topics such as data representation and attribute engineering, which play a crucial role in statistical analysis.
Data Engineer
Data Engineer
A Data Engineer is responsible for designing, constructing, maintaining, and managing data and database systems. This course, Feature Engineering em Português Brasileiro, may be useful to those interested in the growing field of Data Engineering as it delves into topics such as data preprocessing and transformation, which play a crucial role in building and maintaining efficient and effective data systems.
For more career information including salaries, visit:
OpenCourser.com/course/njyyxi/feature
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
Feature Engineering em Português Brasileiro.
Esse livro oferece uma introdução abrangente à engenharia de atributos, cobrindo tópicos como seleção de atributos, transformação e avaliação. Ele também fornece estudos de caso práticos para ilustrar os conceitos discutidos.
Este livro fornece um guia prático para aplicar técnicas de engenharia de atributos usando Python. Ele abrange uma ampla gama de tópicos, incluindo pré-processamento de dados, transformação de atributos e avaliação de modelos.
Embora este livro não se concentre especificamente na engenharia de atributos, ele fornece uma base sólida nos fundamentos da ciência de dados, incluindo conceitos como aprendizado de máquina e análise estatística.
Este livro clássico é uma referência abrangente para métodos estatísticos usados no aprendizado de máquina. Ele fornece uma base sólida na teoria e nas técnicas subjacentes à engenharia de atributos.
Save
Embora este livro não se concentre especificamente na engenharia de atributos, ele fornece uma visão geral acessível do aprendizado de máquina e é um ótimo recurso para entender os conceitos subjacentes.
Embora este livro se concentre principalmente no aprendizado profundo, ele também aborda técnicas de engenharia de atributos usadas em projetos de aprendizado profundo.
Este livro fornece uma introdução abrangente ao uso do Python para análise de dados. Ele cobre vários tópicos, incluindo técnicas de pré-processamento e transformação de dados usadas na engenharia de atributos.
Este livro aborda técnicas avançadas de análise de dados usando o Apache Spark. Ele inclui discussões sobre engenharia de atributos e técnicas de pré-processamento usadas em projetos de big data.
Embora este livro se concentre na engenharia de dados na plataforma Google Cloud, ele também aborda técnicas de engenharia de atributos usadas em projetos de aprendizado de máquina.
Este livro oferece uma visão geral rápida do aprendizado de máquina. Ele aborda brevemente os conceitos básicos da engenharia de atributos.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/njyyxi/feature
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Effort
2 semanas, de 5 a 7 horas por semana
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Português
Transcript
English
This course belongs to a
collection
called
Machine Learning with TensorFlow on Google Cloud em Português Brasileiro. It's comprised of five courses:
- Intro to TensorFlow em Português Brasileiro
- Launching into Machine Learning em Português Brasileiro
- Feature Engineering em Português Brasileiro (viewing)
- Art and Science of Machine Learning em Português Brasileiro
- How Google does Machine Learning em Português Brasileiro
Good to know
Ensina engenharia de atributos para melhorar a precisão de modelos de aprendizado de máquina
Noções básicas e práticas sobre engenharia de atributos usando BigQuery ML, Keras e TensorFlow
Desenvolvido pelo Google Cloud Training, referências reconhecidas na área
Aborda cruzamentos de atributos, relevantes para métodos de aprendizado de máquina atuais
Introdução ao TensorFlow Transform para pré-processamento de dados
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