Deep Learning

SIF121238
Home Program Kelas Sistem Informasi Deep Learning
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Terakhir diupdate:

May 19, 2025

Jumlah SKS:

3 SKS

Deskripsi Mata Kuliah

Mata kuliah ini membahas konsep, teknik, dan algoritma Deep Learning (DL) yang digunakan dalam pengolahan data dan kecerdasan buatan. Mahasiswa akan mempelajari arsitektur neural network, training model dengan backpropagation, serta penerapannya dalam visi komputer, NLP, dan data sequence

Deep Learning

  • Pokok Bahasan / Bahan Kajian
    •

    • Pengantar Deep Learning
    • Perbedaan Machine Learning dan Deep Learning
    • Artificial Neural Network (ANN)
    • Forward Propagation & Backpropagation
    • Activation Functions
    • Optimizer & Loss Function
    • Overfitting, Regularization, Dropout
    • Convolutional Neural Network (CNN)
    • Case Study: Image Classification
    • Recurrent Neural Network (RNN), LSTM
    • Case Study: NLP / Text Classification
    • Transfer Learning
    • Hyperparameter Tuning
    • Interpretability & Explainability
    • Mini Project / Presentasi Akhir

  • Pustaka
    •

  • Goodfellow, Bengio, Courville. Deep Learning, MIT Press, 201
  • Géron, A. Hands-On ML with Scikit-Learn, Keras, and TensorFlow, 2nd Ed., O’Reilly
  • Chollet, F. Deep Learning with Python, Manning, 2017
  • Brownlee, J. Deep Learning for Computer Vision, Machine Learning Mastery
  • Raschka, S. Python Machine Learning, Packt
  • Molnar, C. Interpretable Machine Learning, 2022

    • Slide Presentasi
    Video Pembelajaran
    Google Colab / Jupyter Notebook
    Simulasi Interaktif
    Dataset Publik (MNIST, CIFAR-10, IMDB, dll)
    eBook / Buku Digital
    Learning Management System (LMS).
    Grafik Visualisasi (matplotlib, seaborn, TensorBoard)
    Github

    dosen-deep-learning
    Dwi Rolliawati, M.T
    197909272014032001
    Preview
    • Koordinator :
      Dwi Rolliawati, M.T
    • Dosen Pengajar :1
    • Durasi :1 Semester