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ELINGUI Pascal Uriel
Dans ce projet guidé, vous créerez des modèles de Deep Learning (Apprentissage profond) automatisés facilement en utilisant AutoKeras une bibliothèque basée sur Keras et Tensorflow.
Read more
Dans ce projet guidé, vous créerez des modèles de Deep Learning (Apprentissage profond) automatisés facilement en utilisant AutoKeras une bibliothèque basée sur Keras et Tensorflow.
Read more
Dans ce projet guidé, vous créerez des modèles de Deep Learning (Apprentissage profond) automatisés facilement en utilisant AutoKeras une bibliothèque basée sur Keras et Tensorflow.
L'optimisation des hyper-paramètres et l’une des tâches les plus chronophages lors de la création de modèles de Machine Learning. Avec AutoML cela est automatisé, ce qui résulte en un gain de temps considérable pour les ingénieurs en Machine Learning. Cela permet aussi à n'importe qui ayant des connaissances basiques de rapidement créer un modèle de Machine Learning
Cette compétence est déterminante pour accroître votre productivité et la qualité de vos modèles de machine learning.
Ce cours est destiné aux ingénieurs en Machine Learning, au Data Scientists et tous les curieux désireux augmenter leur productivité.
Register for this course and see more details by visiting:
OpenCourser.com/course/y6jf1m/automl
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What's inside
Syllabus
Project Overview
Dans ce projet guidé, vous créerez des modèles de Deep Learning (Apprentissage profond) très simplement en utilisant AutoKeras une bibliothèque basée sur Keras et Tensorflow.
L'optimisation des hyper-paramètres prend beaucoup de temps lors de la création de modèles de Machine Learning. Avec AutoML cela est automatisé, ce qui permet de gagner un temps considérable.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Supports the development of artificial intelligence models without the necessity for specialized expertise or coding knowledge
AutoML tools enhance efficiency, saving time for machine learning engineers
Suitable for beginners in the field of machine learning or data science who are interested in developing practical skills
Teaches techniques that align with current industry practices, making graduates more competitive in the job market
Save this course
Save AutoML avec AutoKeras - Classification d'images 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 AutoML avec AutoKeras - Classification d'images with these
activities:
Lire "Deep Learning"
Show steps
Élargissez vos connaissances en apprentissage profond en lisant "Deep Learning" pour approfondir votre compréhension des concepts.
View
L'apprentissage profond (French Edition)
on Amazon
Show steps
-
Lire le chapitre 1
Tutoriels sur AutoKeras
Show steps
Suivez des tutoriels sur AutoKeras pour vous familiariser avec ses fonctionnalités et ses utilisations.
Show steps
-
Installer AutoKeras
-
Créer un modèle AutoML avec AutoKeras
-
Régler les hyperparamètres d'AutoKeras
Participer à un groupe d'étude
Show steps
Discutez du contenu du cours et clarifiez les concepts difficiles avec d'autres étudiants.
Browse courses on
Deep Learning
Show steps
-
Rejoindre un groupe d'étude
-
Participer aux discussions
One other activity
Expand to see all activities and additional details
Show all four activities
Contribuer à la communauté AutoKeras
Show steps
Renforcez vos compétences en contribuant à la communauté AutoKeras en soumettant des problèmes ou en proposant des améliorations.
Show steps
-
Identifier un problème ou une zone d'amélioration
-
Créer une demande ou une proposition de pull
-
Soumettre la demande ou la proposition de pull
Lire "Deep Learning"
Show steps
Élargissez vos connaissances en apprentissage profond en lisant "Deep Learning" pour approfondir votre compréhension des concepts.
View
L'apprentissage profond (French Edition)
on Amazon
Show steps
Show steps
Show steps
- Lire le chapitre 1
Tutoriels sur AutoKeras
Show steps
Suivez des tutoriels sur AutoKeras pour vous familiariser avec ses fonctionnalités et ses utilisations.
Show steps
Show steps
Show steps
- Installer AutoKeras
- Créer un modèle AutoML avec AutoKeras
- Régler les hyperparamètres d'AutoKeras
Participer à un groupe d'étude
Show steps
Discutez du contenu du cours et clarifiez les concepts difficiles avec d'autres étudiants.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Rejoindre un groupe d'étude
- Participer aux discussions
One other activity
Expand to see all activities and additional details
Show all four activities
Contribuer à la communauté AutoKeras
Show steps
Renforcez vos compétences en contribuant à la communauté AutoKeras en soumettant des problèmes ou en proposant des améliorations.
Show steps
Show steps
Show steps
- Identifier un problème ou une zone d'amélioration
- Créer une demande ou une proposition de pull
- Soumettre la demande ou la proposition de pull
Career center
Learners who complete AutoML avec AutoKeras - Classification d'images will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists are experts at extracting and interpreting meaningful insights from data. They use statistical and programming techniques to analyze data and draw conclusions from it. This course will help you develop the skills you need to become a successful Data Scientist, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. They work with data scientists to identify the right data and algorithms to use, and then they build and train models that can solve real-world problems. This course will help you develop the skills you need to become a successful Machine Learning Engineer, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data. They use their skills to identify trends and patterns in data, and then they communicate their findings to stakeholders. This course will help you develop the skills you need to become a successful Data Analyst, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Business Analyst
Business Analyst
Business Analysts are responsible for identifying and solving business problems. They use their skills to analyze data, identify trends, and develop solutions that can improve business performance. This course will help you develop the skills you need to become a successful Business Analyst, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, building, and testing software applications. They use their skills to solve real-world problems and create software that is both efficient and user-friendly. This course will help you develop the skills you need to become a successful Software Engineer, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Product Manager
Product Manager
Product Managers are responsible for managing the development and launch of new products. They work with engineers, designers, and marketers to ensure that products meet the needs of customers. This course will help you develop the skills you need to become a successful Product Manager, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Marketing Analyst
Marketing Analyst
Marketing Analysts are responsible for analyzing data to identify trends and patterns in consumer behavior. They use their findings to develop marketing campaigns that are more effective and efficient. This course will help you develop the skills you need to become a successful Marketing Analyst, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data to identify trends and patterns. They use their findings to make investment recommendations and provide advice to clients. This course will help you develop the skills you need to become a successful Financial Analyst, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts are responsible for using mathematical and analytical techniques to solve business problems. They use their skills to improve efficiency and productivity in a variety of industries. This course will help you develop the skills you need to become a successful Operations Research Analyst, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
Actuary
Actuary
Actuaries are responsible for assessing and managing risk. They use their skills to develop insurance policies and other financial products that protect people and businesses from financial loss. This course will help you develop the skills you need to become a successful Actuary, including how to use AutoKeras to create models that can automatically optimize their hyperparameters. This will allow you to save time and create models that are more accurate and efficient.
For more career information including salaries, visit:
OpenCourser.com/course/y6jf1m/automl
Reading list
We've selected nine 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
AutoML avec AutoKeras - Classification d'images .
Covers the fundamentals of deep learning, including neural networks, convolutional neural networks, and recurrent neural networks. Provides a practical introduction to using Keras, a high-level neural networks API, written in Python.
A practical guide to machine learning using Python and popular libraries like Scikit-Learn, Keras, and TensorFlow. Covers a wide range of machine learning algorithms and techniques, with a focus on practical applications.
Provides a rigorous mathematical treatment of machine learning, with a focus on probabilistic models. Covers topics such as Bayesian inference, graphical models, and reinforcement learning. Suitable for advanced learners and researchers.
Save
A classic textbook on pattern recognition and machine learning. Provides a comprehensive overview of the field, with a focus on statistical and probabilistic methods. Suitable for advanced learners and researchers.
Save
An introductory textbook on machine learning. Covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. Provides a gentle introduction to the field, suitable for beginners.
Save
A comprehensive textbook on deep learning. Covers the latest techniques and algorithms in the field, with a focus on mathematical foundations. Suitable for advanced learners and researchers.
Provides a practical introduction to machine learning using the R programming language. Covers a wide range of machine learning algorithms and techniques, with a focus on data analysis and visualization. Suitable for beginners and intermediate learners.
Provides a practical introduction to machine learning using the Python programming language. Covers a wide range of machine learning algorithms and techniques, with a focus on data analysis and visualization. Suitable for beginners and intermediate learners.
Provides a practical introduction to machine learning using the C++ programming language. Covers a wide range of machine learning algorithms and techniques, with a focus on high-performance computing. Suitable for beginners and intermediate learners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/y6jf1m/automl
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Effort
90
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
ELINGUI Pascal Uriel
Language
Français
Good to know
Supports the development of artificial intelligence models without the necessity for specialized expertise or coding knowledge
AutoML tools enhance efficiency, saving time for machine learning engineers
Suitable for beginners in the field of machine learning or data science who are interested in developing practical skills
Teaches techniques that align with current industry practices, making graduates more competitive in the job market
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