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Google Cloud Training
Dans ce cours, vous profiterez de l'expérience d'ingénieurs et de formateurs en ML qui développent des pipelines de ML chez Google Cloud à l'aide de technologies de pointe. Les premiers modules porteront sur TensorFlow Extended (TFX), la plate-forme Google de machine learning de production basée sur TensorFlow et conçue pour gérer des pipelines et des métadonnées de ML. Vous explorerez les composants de pipelines et apprendrez à orchestrer des pipelines avec TFX. Vous verrez également comment automatiser vos pipelines au moyen d'une intégration et d'un déploiement continus, et comment gérer des métadonnées de ML. Ensuite, nous découvrirons comment automatiser et réutiliser des pipelines de ML sur plusieurs frameworks de ML tels que TensorFlow, PyTorch, scikit-learn et XGBoost. Vous apprendrez également à utiliser Cloud Composer, un autre outil Google Cloud, pour orchestrer vos pipelines d'entraînement continu. Enfin, nous verrons comment utiliser MLflow pour gérer l'ensemble du cycle de vie du machine learning.
Register for this course and see more details by visiting:
OpenCourser.com/course/c4qto2/ml
What's inside
Syllabus
Présentation
Ce module présente le plan du cours.
Présentation des pipelines TFX
Ce module présente TensorFlow Extended (TFX), puis aborde les concepts et les composants TFX.
Read more
Syllabus
Présentation
Ce module présente le plan du cours.
Présentation des pipelines TFX
Ce module présente TensorFlow Extended (TFX), puis aborde les concepts et les composants TFX.
Read more
Orchestrer des pipelines avec TFX
Dans ce module, vous allez :
Composants personnalisés et CI/CD pour les pipelines TFX
Métadonnées avec TFX
Ce module traite de l'utilisation de métadonnées TFX pour gérer des artefacts.
Effectuer un entraînement continu avec plusieurs SDK, Kubeflow et AI Platform Pipelines
Ce module traite de l'entraînement continu avec plusieurs SDK, mais aussi avec Kubeflow et AI Platform Pipelines.
Effectuer un entraînement continu avec Cloud Composer
Ce module traite de l'entraînement continu avec Cloud Composer.
Pipelines de ML avec MLflow
Ce module présente MLflow et ses composants.
Résumé
Ce module résume le cours.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Cette formation vous aidera à devenir un expert dans la mise en œuvre de pipelines de ML dans un environnement Google Cloud
Elle est délivrée par Google Cloud Training, vous pouvez donc être sûr que vous apprendrez les dernières techniques et meilleures pratiques
Elle est parfaite pour les ingénieurs ML qui souhaitent automatiser et réutiliser leurs pipelines de ML
Elle couvre un large éventail de sujets, de TensorFlow Extended à MLflow, vous fournissant une vue d'ensemble complète des pipelines de ML
Elle est enseignée par des experts de Google Cloud, vous pouvez donc être sûr d'obtenir des informations de première main
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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 ML Pipelines on Google Cloud - Français with these
activities:
Rafraîchir ses compétences en programmation
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Rafraîchissez vos compétences en programmation avant de commencer le cours.
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Python
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Réviser les concepts de programmation de base
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Résoudre des problèmes de programmation
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Rafraîchir ses compétences en programmation
Show steps
Rafraîchissez vos compétences en programmation avant de commencer le cours.
Browse courses on
Python
Show steps
Show steps
Show steps
- Réviser les concepts de programmation de base
- Résoudre des problèmes de programmation
Show all one activities
Career center
Learners who complete ML Pipelines on Google Cloud - Français will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists collaborate with scientists and business stakeholders to build machine learning and artificial intelligence systems. This often involves designing, training, and deploying machine learning models. This course can be helpful as it introduces TensorFlow Extended (TFX), a platform for managing ML pipelines, models, and metadata. This course also helps with model orchestration and automating pipelines with CI/CD. Moreover, this course covers using MLflow to manage the end-to-end machine learning lifecycle.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and how to use MLflow to manage the machine learning lifecycle.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain the infrastructure and systems that store and process data. This often involves working with big data technologies like Hadoop, Spark, and Hive. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build the skills to manage ML pipelines and metadata.
Software Engineer
Software Engineer
Software Engineers design, develop, test, and deploy software systems. This often involves working with a variety of programming languages, tools, and technologies. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. This often involves working with advanced mathematics and statistics. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions. This often involves working with financial data. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. This often involves working with a variety of statistical methods and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This often involves working with a variety of data analysis tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Business Analyst
Business Analyst
Business Analysts analyze business processes and data to identify opportunities for improvement. This often involves working with a variety of business analysis tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This often involves working with a variety of project management tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Product Manager
Product Manager
Product Managers define, develop, and launch products. This often involves working with a variety of product management tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Sales Manager
Sales Manager
Sales Managers lead and motivate sales teams to achieve sales goals. This often involves working with a variety of sales management tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Marketing Manager
Marketing Manager
Marketing Managers plan and execute marketing campaigns to promote products and services. This often involves working with a variety of marketing tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Human Resources Manager
Human Resources Manager
Human Resources Managers plan and execute human resources programs and policies. This often involves working with a variety of human resources tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
Financial Manager
Financial Manager
Financial Managers plan and execute financial plans and policies. This often involves working with a variety of financial tools and techniques. This course may be useful as it provides an introduction to TensorFlow Extended (TFX) and its components. This course will give you an understanding of how to orchestrate pipelines with TFX and will help you build skills to manage ML pipelines and metadata.
For more career information including salaries, visit:
OpenCourser.com/course/c4qto2/ml
Reading list
We've selected seven 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
ML Pipelines on Google Cloud - Français.
Bien que ce livre ne se concentre pas spécifiquement sur les pipelines de ML, il fournit une base solide pour comprendre les concepts fondamentaux du machine learning, notamment les algorithmes, la préparation des données et l'évaluation des modèles.
Ce livre fournit une introduction pratique à l'apprentissage profond avec Python. Il couvre les réseaux de neurones, les architectures de modèles et les techniques d'entraînement, ce qui peut être bénéfique pour les apprenants souhaitant approfondir leurs connaissances en matière de ML.
Bien qu'il ne se concentre pas sur les pipelines de ML, ce livre fournit un cadre complet pour la compréhension des méthodes statistiques utilisées dans le machine learning. Il peut être utile comme référence approfondie pour les apprenants souhaitant approfondir leurs connaissances en statistique.
Ce livre offre une approche bayésienne du machine learning, couvrant les concepts d'inférence bayésienne, de modèles graphiques et d'optimisation. Il peut être utile aux apprenants intéressés par une compréhension plus théorique du sujet.
Bien qu'il ne se concentre pas sur les pipelines de ML, ce livre fournit une introduction pratique à l'analyse des séries temporelles. Il peut être utile aux apprenants souhaitant explorer les techniques de prévision et de modélisation des données temporelles.
Bien que ce livre ne traite pas spécifiquement des pipelines de ML, il fournit une introduction complète au traitement du langage naturel. Il peut être bénéfique pour les apprenants souhaitant explorer les techniques de traitement et d'analyse du langage naturel.
Save
Bien que ce livre ne se concentre pas sur les pipelines de ML, il fournit une introduction complète à la vision par ordinateur. Il peut être bénéfique pour les apprenants souhaitant explorer les techniques de traitement et d'analyse des images et des vidéos.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/c4qto2/ml
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Effort
3 weeks of study, 6-8 hours/week
Level
Advanced
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Français
Transcript
English
Good to know
Cette formation vous aidera à devenir un expert dans la mise en œuvre de pipelines de ML dans un environnement Google Cloud
Elle est délivrée par Google Cloud Training, vous pouvez donc être sûr que vous apprendrez les dernières techniques et meilleures pratiques
Elle est parfaite pour les ingénieurs ML qui souhaitent automatiser et réutiliser leurs pipelines de ML
Elle couvre un large éventail de sujets, de TensorFlow Extended à MLflow, vous fournissant une vue d'ensemble complète des pipelines de ML
Elle est enseignée par des experts de Google Cloud, vous pouvez donc être sûr d'obtenir des informations de première main
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