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# Python package requirements for FOMO Workshop Tutorials
# Covers all 4 tutorials: Data Cleaning, Fine-Tuning, Uncertainty Quantification, Latent Space Analysis
# ============================================================
# CORE SCIENTIFIC COMPUTING
# ============================================================
numpy>=1.21.0
pandas>=1.3.0
scipy>=1.7.0
# ============================================================
# MACHINE LEARNING & DEEP LEARNING
# ============================================================
torch>=2.0.0
transformers>=4.30.0
datasets>=2.0.0
scikit-learn>=1.0.0
# Parameter-efficient fine-tuning (Tutorial 2)
peft>=0.4.0
# ============================================================
# DIMENSIONALITY REDUCTION & OPTIMIZATION
# ============================================================
# UMAP for visualization (Tutorial 4)
umap-learn>=0.5.3
# Hyperparameter optimization (Tutorial 4)
optuna>=3.0.0
# ============================================================
# PLOTTING & VISUALIZATION
# ============================================================
matplotlib>=3.4.0
seaborn>=0.11.0
# For interactive Optuna plots (Tutorial 4)
plotly>=5.0.0
# ============================================================
# UTILITIES
# ============================================================
# Progress bars
tqdm>=4.62.0
# HTTP requests for data downloading
requests>=2.26.0
# ============================================================
# JUPYTER SUPPORT
# ============================================================
ipykernel>=6.0.0
jupyterlab>=3.0.0
# ============================================================
# OPTIONAL: GPU ACCELERATION
# ============================================================
# Uncomment if you have CUDA-capable GPU:
# torch>=2.0.0+cu118 -f https://download.pytorch.org/whl/torch_stable.html
# ============================================================
# INSTALLATION NOTES
# ============================================================
# Install all packages:
# pip install -r requirements.txt
#
# For GPU support, install PyTorch with CUDA first:
# pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
# pip install -r requirements.txt