Detail Mata kuliah

Deep Learning

SIF121238

Deep Learning

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

Pokok Bahasan

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

Media Pembelajaran

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

Deep Learning

Deep Learning

Deskripsi Mata Kuliah

Pokok Bahasan

Pustaka

Media Pembelajaran

Level Mata Kuliah:

Koordinator Mata Kuliah:

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Mata Kuliah MBKM:

Akademik

Tentang UINSA

Informasi

UINSA

UIN Sunan Ampel Surabaya

Kampus Ahmad Yani

Kampus Gunung Anyar