Development Environment Setup
Complete instructions for installing core tools, dependencies, and infrastructure requirements for AI development
Local Setup
- • Python 3.10+ installation
- • PyTorch/TensorFlow dependency management
- • Jupyter environment configuration
Cloud Configuration
- • AWS/GCP instance provisioning
- • GPU resource allocation
- • Remote SSH access setup
Local Development Setup
Install Python
Install the latest Anaconda distribution or native Python 3.10
Python 3.10.13 64-bit
PyPI Package Support
Installation Steps
- Download from official repository
- Verify GPG signature
- Install with full development headers
Python Installation Verification
python --version
# Should output Python 3.10.0 or higher
Setup Virtual Environment
Create isolated development environments for dependency management
venv
Conda
pipenv
Basic Environment
python -m venv ai-env
source ai-env/bin/activate
pip install numpy pandas
GPU Support Verification
nvidia-smi
# Confirm CUDA driver version
Cloud Resource Configuration
Provision Cloud Instance
Recommended Configuration
- • 16GB RAM minimum
- • NVIDIA A100 GPU or equivalent
- • Ubuntu 22.04 LTS
AWS EC2 Setup
aws ec2 run-instances \
--image-id ami-0c9a428b8d8988c4f \
--instance-type p3.2x
SSH Connection
ssh -i "my-key.pem" ubuntu@[ip]
Essential Development Tools
Jupyter Lab
Interactive development environment for notebooks and data exploration
Configuration Guide →