AutoML Project Setup

Prerequisites

• Python 3.11

• Conda (Miniconda or Anaconda)

• NVIDIA GPU (optional, for GPU acceleration)

• CUDA-compatible drivers installed on your system

1. Create and Activate a Conda Environment

conda create -n automl python=3.11 cudatoolkit=11.3 -y

conda activate automl

2. Install PyTorch

Install the CUDA-enabled version of PyTorch:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126

Note: Ensure the selected PyTorch/CUDA version is compatible with your GPU drivers.

3. Upgrade Packaging Tools

pip install --upgrade pip setuptools wheel

4. Install AutoGluon

pip install autogluon

5. Install Project Dependencies

pip install -r requirements.txt

6. Launch the Application

Start the Streamlit application:

streamlit run app.py

Verify Installation

To confirm that PyTorch can access your GPU:

python -c "import torch; print(torch.cuda.is_available())"

Expected output:

True

---

Quick Setup

conda create -n automl python=3.11 cudatoolkit=11.3 -y

conda activate automl



pip install --upgrade pip setuptools wheel

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126

pip install autogluon

pip install -r requirements.txt



streamlit run app.py