Apprentissage automatique

Les cours Apprentissage automatique se concentrent sur la création de systèmes pour utiliser des ensembles de données volumineux et apprendre à partir de ces ensembles. Les thèmes d'étude incluent les algorithmes prédictifs, le traitement de langage naturel et la reconnaissance de formes statistiques.

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Deep Learning

Deep Learning

deeplearning.ai
Spécialisation
Noté 4.8 sur cinq étoiles.
IBM AI Foundations for Business

IBM AI Foundations for Business

IBM
Spécialisation
Noté 4.7 sur cinq étoiles.
Applied Data Science

Applied Data Science

IBM
Spécialisation
Noté 4.6 sur cinq étoiles.
Data Science: Foundations using R

Data Science: Foundations using R

Johns Hopkins University
Spécialisation
Noté 4.6 sur cinq étoiles.
Natural Language Processing

Natural Language Processing

deeplearning.ai
Spécialisation
Noté 4.6 sur cinq étoiles.
TensorFlow in Practice

TensorFlow in Practice

deeplearning.ai
Spécialisation
Noté 4.7 sur cinq étoiles.
Data Engineering, Big Data, and Machine Learning on GCP

Data Engineering, Big Data, and Machine Learning on GCP

Google Cloud
Spécialisation
Noté 4.6 sur cinq étoiles.
Mathematics for Machine Learning

Mathematics for Machine Learning

Imperial College London
Spécialisation
Noté 4.4 sur cinq étoiles.
Reinforcement Learning

Reinforcement Learning

University of Alberta
Spécialisation
Noté 4.7 sur cinq étoiles.
AI for Medicine

AI for Medicine

deeplearning.ai
Spécialisation
Noté 4.7 sur cinq étoiles.
Machine Learning with TensorFlow on Google Cloud Platform

Machine Learning with TensorFlow on Google Cloud Platform

Google Cloud
Spécialisation
Noté 4.5 sur cinq étoiles.
Advanced Machine Learning

Advanced Machine Learning

National Research University Higher School of Economics
Spécialisation
Noté 4.4 sur cinq étoiles.
Big Data

Big Data

University of California San Diego
Spécialisation
Noté 4.5 sur cinq étoiles.
Investment Management with Python and Machine Learning

Investment Management with Python and Machine Learning

EDHEC Business School
Spécialisation
Noté 4.3 sur cinq étoiles.
Машинное обучение и анализ данных

Машинное обучение и анализ данных

Moscow Institute of Physics and Technology
Spécialisation
Noté 4.7 sur cinq étoiles.
Data Science: Statistics and Machine Learning

Data Science: Statistics and Machine Learning

Johns Hopkins University
Spécialisation
Noté 4.4 sur cinq étoiles.

    Questions fréquentes sur Apprentissage automatique

  • Machine learning is a branch of artificial intelligence that seeks to build computer systems that can learn from data without human intervention. These powerful techniques rely on the creation of sophisticated analytical models that are “trained” to recognize patterns within a specific dataset before being unleashed to apply these patterns to more and more data, steadily improving performance without further guidance.

    For example, machine learning is making increasingly accurate image recognition algorithms possible. Human programmers provide a relatively small set of images that are labeled as “cars” or “not cars,” for instance, and then expose the algorithms to vastly larger numbers of images to learn from. While the iterative algorithms typically used in machine learning aren’t new, the power of today’s computing systems have enabled this method of data analysis to become more effective more rapidly than ever.