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Setup Optimal Environment untuk Deep Learning Fibonacci Trading

Panduan Lengkap - June 12, 2025

🎯 Tujuan

  • Install Anaconda dengan Python 3.11 (optimal untuk TensorFlow)
  • Setup environment khusus deep learning
  • Install semua dependencies yang diperlukan
  • Restart enhanced analysis dengan performa maksimal

📋 Step-by-Step Installation Guide

Step 1: Download dan Install Anaconda

  1. Download Anaconda

  2. Install Anaconda

    • Run installer sebagai Administrator
    • Pilih: "Add Anaconda to PATH" ✅
    • Pilih: "Register Anaconda as default Python" ✅
    • Install location: C:\Anaconda3\ (recommended)

Step 2: Verify Installation

Setelah install, buka Anaconda Prompt dan test:

# Check conda version
conda --version

# Check Python version
python --version

# List environments
conda env list

Step 3: Create Dedicated Environment

# Create environment khusus untuk deep learning fibonacci
conda create -n fibonacci_dl python=3.11 -y

# Activate environment
conda activate fibonacci_dl

# Verify Python version
python --version  # Should show Python 3.11.x

Step 4: Install Core Packages

# Install essential scientific packages
conda install numpy pandas scikit-learn matplotlib seaborn jupyter -y

# Install TensorFlow dengan GPU support (optional)
pip install tensorflow[and-cuda]

# Alternative: CPU-only TensorFlow
pip install tensorflow

# Install additional ML packages
pip install mlflow optuna hyperopt

# Install trading-specific packages
pip install yfinance ta-lib pandas-ta

# Install utilities
pip install tqdm pyyaml python-dotenv

Step 5: Verify TensorFlow Installation

# Test TensorFlow
python -c "
import tensorflow as tf
print('TensorFlow version:', tf.__version__)
print('GPU available:', tf.config.list_physical_devices('GPU'))
print('✅ TensorFlow ready!')
"

🏗️ Project Structure Optimal

fibonacci_deep_learning/
├── environment.yml           # Conda environment file
├── requirements.txt          # Pip requirements
├── setup_environment.py      # Automated setup script
├── data/
│   ├── raw/                 # Original CSV files
│   ├── processed/           # Cleaned data
│   └── features/            # ML features
├── models/
│   ├── tensorflow/          # TensorFlow models
│   ├── sklearn/             # Scikit-learn models
│   └── saved/               # Trained models
├── notebooks/               # Jupyter analysis
├── src/
│   ├── data/               # Data processing
│   ├── models/             # Model architectures
│   ├── training/           # Training pipelines
│   └── utils/              # Utilities
├── experiments/            # MLflow tracking
├── reports/                # Analysis reports
└── deployment/             # Production code

🎯 Next Steps After Installation

  1. Restart Computer (to ensure PATH updates)
  2. Open Anaconda Prompt
  3. Navigate to project: cd E:\aiml\MLFLOW
  4. Activate environment: conda activate fibonacci_dl
  5. Run setup script: python setup_optimal_environment.py

⚠️ Important Notes

  • Uninstall old Python: Windows Settings → Apps → Python 3.13.4 → Uninstall
  • Use Anaconda Prompt: Always use Anaconda Prompt, bukan Command Prompt biasa
  • Environment isolation: Selalu activate fibonacci_dl environment sebelum coding
  • GPU support: Jika punya NVIDIA GPU, install CUDA toolkit untuk performa maksimal

🔧 Troubleshooting

Jika TensorFlow gagal install:

pip install --upgrade pip
pip install tensorflow --no-cache-dir

Jika import error:

conda update --all
pip install --upgrade tensorflow

Jika environment conflict:

conda remove -n fibonacci_dl --all
# Repeat Step 3-4

Ready? Mari kita mulai installation! 🚀