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  1. What is semi-supervised learning? - IBM

    Jun 17, 2019 · Semi-supervised learning is a type of machine learning that combines supervised and unsupervised learning by using labeled and unlabeled data to train AI models.

  2. 什么是半监督学习?| IBM

    半监督学习是一种结合了监督学习和无监督学习的机器学习,使用标记数据和未标记数据来训练 AI 模型。

  3. 半教師あり学習とは | IBM

    半教師あり学習は、教師あり学習と教師なし学習を組み合わせた機械学習の一種で、ラベル付きデータとラベルなしデータを使用して、AIモデルをトレーニングします。

  4. What is supervised learning? - IBM

    Supervised learning is a machine learning technique that uses labeled data sets to train artificial intelligence algorithms models to identify the underlying patterns and relationships between …

  5. Qu’est-ce que l’apprentissage semi-supervisé - IBM

    L’apprentissage semi-supervisé est un type de machine learning qui combine l’apprentissage supervisé et non supervisé, en utilisant des données étiquetées et non étiquetées pour …

  6. What is self-supervised learning? - IBM

    Jan 5, 2021 · Self-supervised learning is a machine learning technique that uses unsupervised learning for tasks that conventionally require supervised learning. Rather than relying on …

  7. Was ist halbüberwachtes Lernen? - IBM

    Halbüberwachtes Lernen ist eine Art des maschinellen Lernens, bei dem überwachtes und unüberwachtes Lernen kombiniert werden, wobei gelabelte und nicht gelabelte Daten zum …

  8. Supervised versus unsupervised learning: What's the difference?

    Semi-supervised learning is a happy medium, where you use a training data set with both labeled and unlabeled data. It’s particularly useful when it’s difficult to extract relevant features from …

  9. ¿Qué es el aprendizaje semisupervisado? - IBM

    El aprendizaje semisupervisado es un tipo de machine learning que combina el aprendizaje supervisado y no supervisado, utilizando datos etiquetados y no etiquetados para entrenar a …

  10. O que é aprendizado semissupervisionado? - IBM

    Aprendizado semissupervisionado é um tipo de aprendizado de máquina que combina aprendizado supervisionado e não supervisionado, usando dados rotulados e não rotulados …