Art and Science of Machine Learning en Français from Coursera

What's inside

Syllabus

Présentation

Bienvenue dans "Art and Science of Machine Learning". Dans ce cours, nous allons voir les compétences essentielles que sont l'intuition, le bon sens et l'expérimentation, nécessaires pour ajuster vos modèles de ML et optimiser leurs performances. Nous verrons comment généraliser votre modèle à l'aide de techniques de régularisation, et nous évoquerons les effets des hyperparamètres tels que la taille de lot et le taux d'apprentissage sur les performances de votre modèle. Nous présenterons également certains des algorithmes d'optimisation les plus courants et vous montrerons comment spécifier une méthode d'optimisation dans votre code TensorFlow.

L'art du ML

Dans ce module, vous allez apprendre à régler la taille de lot et le taux d'apprentissage pour améliorer les performances du modèle, à optimiser votre modèle et à appliquer les concepts au code TensorFlow.

Réglages des hyperparamètres

Dans ce module, vous allez apprendre à faire la différence entre les paramètres et les hyperparamètres. Ensuite, nous aborderons l'approche traditionnelle de recherche de réseaux et verrons comment aller plus loin grâce à des algorithmes plus intelligents. Enfin, vous découvrirez à quel point Cloud ML Engine facilite l'automatisation des réglages des hyperparamètres.

Un soupçon de science

Dans ce module, nous allons évoquer la science qui accompagne l'art du machine learning. Nous allons d'abord découvrir comment effectuer la régularisation à des fins de parcimonie pour parvenir à des modèles plus simples et plus concis. Ensuite, nous verrons ce qu'est la régression logistique et comment déterminer les performances.

La science des réseaux de neurones

Dans ce module, nous allons approfondir l'aspect scientifique du ML, en particulier les réseaux de neurones.

Représentations vectorielles continues

Dans ce module, vous apprendrez à utiliser les représentations vectorielles continues pour gérer des données creuses, afin que les modèles de machine learning utilisant des données creuses consomment moins de mémoire et s'entraînent plus rapidement. Les représentations vectorielles continues permettent également d'effectuer une réduction de la dimensionnalité, et ainsi de rendre les modèles plus simples et plus généralisables.

Résumé

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by recognized industry experts from Google

Teaches in-demand skills used across several high-growth sectors

Develops essential machine learning skills

Covers key topics in machine learning, such as model tuning, hyperparameter optimization, and regularization techniques

Includes hands-on labs and interactive materials

Requires prior knowledge of coding and machine learning

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 Art and Science of Machine Learning en Français with these activities:

Review Hyperparameter search

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Reviewing the basics of hyperparameter search will help you understand how to adjust your models' hyperparameters to improve performance.

Browse courses on Hyperparameter Tuning

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Read about hyperparameter search algorithms
Practice using a hyperparameter search library

Complete practice exercises on optimizing machine learning models

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Completing practice exercises on optimizing machine learning models will help you develop your skills and improve your understanding of the concepts.

Browse courses on Machine Learning Optimization

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Find practice exercises online or in a textbook
Complete the exercises as best as you can
Review your answers and learn from your mistakes

Follow a tutorial on advanced optimization algorithms

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Following a tutorial on advanced optimization algorithms will help you learn about the latest techniques for optimizing your models.

Browse courses on Optimization Algorithms

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Find a tutorial on an optimization algorithm that interests you
Follow the tutorial step-by-step
Implement the algorithm in your own code

Eight other activities

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Ajuster la taille du lot et le taux d'apprentissage

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Perfectionnez vos compétences pour modifier la taille du lot et le taux d'apprentissage afin d'optimiser les performances du modèle.

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Expérimentez avec différentes tailles de lot et observez leurs effets sur l'entraînement du modèle.
Ajustez le taux d'apprentissage pour trouver une valeur qui minimise la perte et améliore la précision.

Appliquer les concepts de régularisation

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Créez un modèle qui utilise les techniques de régularisation pour améliorer ses performances et réduire le sur-apprentissage.

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Appliquez la régularisation L1 ou L2 à votre modèle et observez l'impact sur la complexité et les performances du modèle.
Ajustez les hyperparamètres de régularisation pour obtenir des performances optimales.

Tutoriels avancés sur TensorFlow

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Explorez des tutoriels avancés qui approfondissent les concepts et les techniques de TensorFlow pour améliorer votre maîtrise de l'outil.

Browse courses on TensorFlow

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Identifiez les tutoriels qui couvrent des sujets avancés de TensorFlow.
Suivez les tutoriels, expérimentez les concepts et appliquez-les à vos propres projets.

Attend a workshop on machine learning optimization

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Attending a workshop on machine learning optimization will allow you to learn from experts and get hands-on experience with optimization techniques.

Browse courses on Machine Learning Optimization

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Find a workshop that interests you
Register for the workshop
Attend the workshop and participate actively
Follow up with the workshop organizers or speakers after the event

Contribution à un projet d'apprentissage automatique open source

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Participez à un projet d'apprentissage automatique open source pour mettre vos compétences en pratique et élargir vos connaissances.

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Rechercher un projet open source lié à l'apprentissage automatique auquel vous souhaitez contribuer.
Identifiez un problème ou une fonctionnalité sur lequel vous pouvez apporter votre contribution.
Communiquez avec les responsables du projet pour proposer votre contribution.
Travaillez sur votre contribution et soumettez une demande d'extraction.

Blog sur les applications réelles de l'apprentissage automatique

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Créez un blog qui explore les applications du monde réel de l'apprentissage automatique pour approfondir votre compréhension et la partager avec les autres.

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Recherchez et identifiez des exemples d'applications d'apprentissage automatique dans divers domaines.
Analysez les cas d'utilisation, les défis et les avantages de chaque application.
Rédigez des articles de blog clairs et concis qui expliquent les concepts et les implications de ces applications.

Write a blog post or article on machine learning optimization

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Writing a blog post or article on machine learning optimization will help you solidify your understanding of the concepts and share your knowledge with others.

Browse courses on Machine Learning Optimization

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Choose a topic that you are knowledgeable about
Research the topic thoroughly
Write a clear and concise article
Publish your article on a blog or website

Participate in a machine learning optimization competition

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Participating in a machine learning optimization competition will challenge you to apply your skills and learn from others.

Browse courses on Machine Learning Optimization

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Find a competition that interests you
Register for the competition
Develop a model and submit it to the competition
Track your progress and learn from others

Career center

Learners who complete Art and Science of Machine Learning en Français will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers design, build, and maintain machine learning systems. They work with data scientists to develop machine learning models, and they work with software engineers to integrate machine learning models into software applications. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Machine Learning Engineer. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to deploy machine learning models into production.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use machine learning and other techniques to solve business problems. They work with data to extract insights and build models that can make predictions or recommendations. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Data Scientist. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Data Scientist

Software Engineer

Software Engineers design, build, and maintain software applications. They work with machine learning engineers to integrate machine learning models into software applications. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Software Engineer. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to deploy machine learning models into production.

See salaries and explore the career path for Software Engineer

Product Manager

Product Managers are responsible for the development and launch of new products. They work with engineers, designers, and marketers to bring new products to market. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Product Manager. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Product Manager

Business Analyst

Business Analysts are responsible for understanding the business needs of an organization and developing solutions to meet those needs. They work with stakeholders to gather requirements, analyze data, and develop recommendations. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Business Analyst. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Business Analyst

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data. They work with data scientists to develop machine learning models, and they work with business analysts to develop solutions to business problems. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Data Analyst. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Data Analyst

Marketing Analyst

Marketing Analysts are responsible for analyzing marketing data and developing marketing campaigns. They work with product managers to develop new products, and they work with sales teams to close deals. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Marketing Analyst. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Marketing Analyst

Sales Engineer

Sales Engineers are responsible for selling and supporting software products. They work with customers to understand their needs and develop solutions that meet those needs. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Sales Engineer. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Sales Engineer

Quantitative Analyst

Quantitative Analysts are responsible for developing and using mathematical models to analyze financial data. They work with traders and portfolio managers to make investment decisions. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Quantitative Analyst. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts are responsible for analyzing financial data and developing financial models. They work with companies to make investment decisions. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Financial Analyst. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Financial Analyst

Actuary

Actuaries are responsible for assessing and managing risk. They work with insurance companies and other financial institutions to develop and price insurance products. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Actuary. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Actuary

Operations Research Analyst

Operations Research Analysts are responsible for developing and using mathematical models to solve business problems. They work with companies to improve their operations and make better decisions. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Operations Research Analyst. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Operations Research Analyst

Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data. They work with scientists, engineers, and other professionals to make decisions based on data. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Statistician. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Statistician

Data Architect

Data Architects are responsible for designing and managing data systems. They work with data scientists and other professionals to ensure that data is stored and managed in a way that supports the needs of the organization. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Data Architect. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Data Architect

Database Administrator

Database Administrators are responsible for managing and maintaining databases. They work with data architects to ensure that databases are configured and maintained in a way that supports the needs of the organization. The Art and Science of Machine Learning en Français course can help you develop the skills you need to become a successful Database Administrator. You will learn about the different types of machine learning algorithms, how to train and evaluate models, and how to apply machine learning to real-world problems.

See salaries and explore the career path for Database Administrator