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    • Iris – #1
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  • Q & A
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    • Build, train NN
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      • Build, compile and train ML models
      • Preprocess data
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      • Sequential models
      • Binary classification
      • Multi-class categorization
      • Plot loss and accuracy
      • Strategies to prevent overfitting
      • Pretrained models
      • Extract features from pre-trained models
      • Correct shape
      • Shape of test data
      • Ensure that you can match test data to the input shape of a neural network
      • Batch
      • Callbacks to trigger the end of training cycles
      • Use datasets from different sources
      • json and csv
      • Use datasets from tf.data.datasets
      • Ensure you can match output data of a neural network to specified input shape for test data
    • NLP
      • Build NLP
      • Prepare text
      • Binary categorization
      • Multi-class categorization
      • Use word embeddings
      • LSTMs
      • RNN and GRU layers
      • RNNS, LSTMs, GRUs and CNNs
      • Train LSTMs
    • Image classification
      • CNN with Conv2D and pooling
      • Process real-world image datasets
      • How to use convolutions
      • Use real-world images
      • Image augmentation
      • ImageDataGenerator
      • Understand how ImageDataGenerator labels images
    • Time series, sequences and predictions
      • Train, tune and use time series
      • Prepare data
      • Understand MAE
      • RNNs and CNNs
      • Trailing versus centred windows
      • TensorFlow for forecasting
      • Prepare features and labels
      • Identify and compensate for sequence bias
      • Adjust the learning rate
Accueil » Forums » Aurélien Géron

Mot-clé du sujet : Aurélien Géron

Atelier de formation à DINARD ChatGPT, MidJourney › Forums › Mot-clé du sujet : Aurélien Géron

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    • Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow

      Démarré par : jboscher dans : Références bibliographiques Tf

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    • il y a 3 années et 1 mois

      jboscher

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