Ide
- Memprediksi output nilai kategorik berdasarkan output
Contoh
- Klasifikasi wajah
- Klasifikasi gambar
- Klasifikasi emosi
- Analisis sentimen
- 1. Intro
- 1.1 Apa itu Machine Learning ?
- 1.2 Apa itu Deep Learning ?
- 1.3 Pengaplikasian di Dunia Nyata
- 1.4 Hello Machine Learning
- 1.5 Bentuk Experience
- 1.6 Supervised Learning
- 1.7 Regression
- 1.8 Classification
- 1.9 Self-Supervised Learning
- 1.10 Unsupervised Learning
- 1.11 Clustering
- 1.12 Dimensionality Reduction
- 1.13 Recommendation System
- 1.14 Semi-supervised Learning
- 1.15 Generative Model
- 1.16 Reinforcement Learning
- 1.17 Lowongan Kerja
- 1.18 Referensi Pembelajaran
- 2. Implementasi
- 2.1 Kesehatan
- 2.2 Pendidikan
- 2.3 Keislaman
- 2.4 Sosial
- 2.5 Pertahanan dan Keamanan
- 2.6 Marketing
- 2.7 Farmasi
- 2.8 Biologi
- 2.9 Keuangan
- 2.10 Kebencanaan
- 2.11 Agrikultur
- 2.12 Energi
- 2.13 Industri
- 2.14 Media Sosial
- 2.15 Robotika
- 2.16 Kewilayahan
- 2.17 Cybersecurity
- 2.18 Seni
- 2.19 Pemerintahan
- 2.20 Personalisasi
- 2.21 Transportasi
- 2.22 Rekreasi
- 3. Perangkat Lunak
- 4. Machine Learning Pipeline
- 4.1 Business Understanding
- 4.2 Data understanding
- 4.3 Literature Review
- 4.4 Data Collection
- 4.5 Exploratory Data Analysis
- 4.6 Data Preprocessing
- 4.7 Feature Engineering
- 4.8 Model Training
- 4.9 Hyperparameter Tuning
- 4.10 Model Testing
- 4.11 System Design
- 4.12 System Development
- 4.13 Model Deployment
- 4.14 Penulisan Artikel Ilmiah dan Publikasi
- 5. Pengetahuan Dasar
- 6. Regression