Bootcamp Machine Learning with Python

Materi dalam Kelas :

• 1
  Pengenalan Machine Learning & Python Fundamental
  Apa itu Machine Learning & use case nya

  Supervised vs Unsupervised Learning

  Setup environment (Google Colab / Jupyter)

  Python fundamental: Variabel & tipe data

  Python fundamental: List, Dictionary

  Python fundamental: Loop & Function

  Python fundamental: Import library
• 2
  Data Preparation dengan Python
  Struktur data tabular

  Import dataset (CSV)

  Handling missing values

  Encoding data kategorikal

  Normalization & Standardization

  Split data (train & test)
• 3
  Machine Learning Pipeline & Evaluasi Model
  Machine Learning workflow end-to-end

  Feature & target

  Training vs Testing

  Evaluasi model Regression: MAE, MSE

  Evaluasi model Classification: Accuracy, Confusion Matrix
• 4
  Supervised Learning: Regression
  Konsep Regression

  Linear Regression

  Multiple Linear Regression

  Overfitting & Underfitting (konseptual)
• 5
  Supervised Learning: Classification
  Konsep Classification

  Logistic Regression

  Decision Tree

  Evaluasi: Precision, Recall, F1-score

  K-Nearest Neighbor (KNN)
• 6
  Unsupervised Learning
  Konsep Unsupervised Learning

  Clustering dengan K-Means

  Menentukan jumlah cluster (Elbow Method)

  PCA (pengenalan konsep)

  Penjelasan Final Project
• 7
  Model Improvement & Best Practice Machine Learning
  Feature scaling & selection (konsep)

  Hyperparameter tuning (GridSearch sekilas)

  Data leakage

  Deployment overview (konsep, non teknis)