floydhub/dl-setup resource

Health v2 · maintenance only

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Adoption not part of the score

1963 stars · 318 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A detailed step-by-step guide for setting up a Linux machine for deep learning research, covering Nvidia drivers, CUDA, cuDNN, Python packages, and frameworks like TensorFlow, Caffe, Theano, Keras, and Torch. It is documentation rather than software, tested on Ubuntu 14.04 with an Nvidia Titan X.

Use cases

• set up a deep learning machine from scratch on ubuntu
• install nvidia drivers and cuda for gpu deep learning
• install cudnn and tensorflow on a fresh linux box
• guide to installing caffe theano keras and torch
• configure a gpu workstation for deep learning research
• setup instructions for deep learning environment

When to choose

• you are building a fresh Ubuntu GPU box for deep learning and want a single walkthrough
• you need driver, CUDA, and cuDNN installation steps in one place
• you want framework-by-framework install notes for older deep learning stacks

When to avoid

• you use modern Ubuntu versions or recent CUDA releases - the guide targets Ubuntu 14.04 and 2016-era drivers
• you want a maintained tool or script rather than a static tutorial
• you need current framework versions like PyTorch or recent TensorFlow builds

Facets

learning-resource · maturity abandoned

developer-tools documentation machine-learning gpu-computing deep-learning machine-learning gpu-computing tutorials operating-systems setup-guide nvidia-drivers cuda cudnn tensorflow caffe theano keras torch deep-learning-machine linux ubuntu

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markdown · JSON · MCP: product_card(name="floydhub/dl-setup")