rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Deep learning
    sub title: a beginners' guide
  name:
    name part: Meedeniya, Dulani
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: EBSCOhost
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2024
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  table of contents: 1 Introduction -- 1.1 Data-Driven Decision-Making and Society -- 1.2 Overview of Deep Learning -- 1.3 Bias and Variance -- 1.3.1 Skewness of Data -- 1.3.2 Bias -- 1.3.3 Variance -- 1.3.4 Trade-Off Between Bias and Variance -- 1.4 Supervised and Unsupervised Learning -- 1.5 Supportive Tools and Libraries -- 1.5.1 TensorFlow -- 1.5.2 Keras -- 1.5.3 PyTorch -- 1.5.4 Jupyter Notebook -- 1.5.5 NumPy and Pandas -- 1.5.6 Tensor Hub -- Review Questions
  table of contents: 2 Concepts and Terminology -- 2.1 Understanding Neural Networks -- 2.2 Regression -- 2.2.1 Linear Regression -- 2.2.2 Logistic Regression -- 2.2.3 Other Regression Methods -- 2.3 Classification -- 2.4 Hyperparameters -- 2.4.1 Overview -- 2.4.2 Weight Initialization -- 2.4.3 Activation Function -- 2.4.4 Learning Rate -- 2.4.5 Loss Function -- 2.4.6 Other Hyperparameters -- 2.5 Model Training -- 2.5.1 Model Selection -- 2.5.2 Model Convergence -- 2.5.3 Overfitting and Underfitting -- 2.5.4 Regularization -- 2.5.5 Network Gradients -- Review Questions
  table of contents: 3 State-Of-The-Art Deep Learning Models: Part I -- 3.1 Overview of Neural Networks -- 3.2 Artificial Neural Networks -- 3.3 Recurrent Neural Network (RNN) -- 3.4 Convolutional Neural Networks -- 3.4.1 Overview of Convolutional Neural Network -- 3.4.2 Concepts of CNN -- 3.4.3 Convolutional Layer -- 3.4.4 Pooling Layer -- 3.4.5 Fully Connected Layer -- 3.5 Comparison of ANN, RNN, and CNN -- Review Questions -- 4 State-Of-The-Art Deep Learning Models: Part II -- 4.1 Feed-Forward Neural Network -- 4.2 Multi-Layer Perceptrons -- 4.3 Generative Adversarial Network (GAN) -- 4.4 Variations of CNNs
  table of contents: 4.4.1 Residual Networks (ResNet) -- 4.4.2 Inception Model -- 4.4.3 GoogLeNet -- 4.4.4 Xception Model -- 4.4.5 DenseNet Model -- 4.4.6 MobileNet Model -- 4.4.7 VGG Model -- 4.4.8 Comparison of CNN Architectures -- 4.5 Capsule Network -- 4.6 Autoencoders -- 4.7 Transformers -- Review Questions -- 5 Advanced Learning Techniques -- 5.1 Transfer Learning -- 5.1.1 Overview of Transfer Learning -- 5.1.2 Transfer Learning Process -- 5.1.3 Transfer Learning Types, Categories, and Strategies -- 5.1.4 Transfer Learning Applications -- 5.1.5 Transfer Learning Challenges -- 5.2 Reinforcement Learning
  table of contents: 5.2.1 Overview of Reinforcement Learning -- 5.2.2 Reinforcement Learning Process -- 5.2.3 Implementation and Scheduling Types -- 5.2.4 Applications of Reinforcement Learning -- 5.2.5 Challenges of Reinforcement Learning -- 5.3 Federated Learning -- 5.3.1 Overview of Federated Learning -- 5.3.2 Federated Learning Process -- 5.3.3 Types and Properties of Federated Learning -- 5.3.4 Applications of Federated Learning -- 5.3.5 Challenges of Federated Learning -- 5.4 Multi-Modeling With Ensemble Learning -- 5.4.1 Overview of Ensemble Learning -- 5.4.2 Ensemble Learning Process -- 5.4.3 Ensemble Learning Techniques
  note: Dulani Meedeniya.
  note: Includes bibliographical references and index.
  subject:
    topic: Deep learning (Machine learning)
  subject:
    topic: Apprentissage profond
  classification: Q325.73 .M44 2024
  classification: 006.3/1
  related item:
    title info:
      title: Deep learning
    name:
      name part: Meedeniya, Dulani.
    origin info:
      publisher: Boca Raton : Taylor and Francis, 2024
      edition: First edition.
    identifier: (DLC) 2023007089
  identifier: 9781003390824
  identifier: 100339082X
  identifier: 9781000924053
  identifier: 100092405X
  identifier: 9781000924060
  identifier: 1000924068
  identifier: 9781032473246
  identifier: 9781032487960
  identifier: 2023007090
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: DLC
    record creation date: 230706
    record change date: 20240209144343.9
    record identifier: in00004779029
    language of cataloging:
      language term: eng