---
title: TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu Reviews
meta_title: 'TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu Reviews
  2026: Details, Pricing, & Features | G2'
meta_description: Filter reviews by the users' company size, role or industry to find
  out how TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu works
  for a business like yours.
date_modified: '2026-04-07'
parent_category:
  name: Marketplace Apps
  url: https://www.g2.com/categories/marketplace-apps
---

# TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu Reviews
**Vendor:** Jetware  
**Category:** [AWS Marketplace Software](https://www.g2.com/categories/aws-marketplace)
## About TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu
The "TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu" Amazon Machine Image (AMI) is a pre-configured environment designed to streamline the development and deployment of deep learning applications. This AMI integrates TensorFlow 1.5 with Python 3.6, optimized for NVIDIA GPUs using CUDA 9.1, all within an Ubuntu operating system. Key Features and Functionality: - Pre-Configured Environment: Eliminates the need for manual setup by providing a ready-to-use deep learning framework. - TensorFlow 1.5 Integration: Offers compatibility with models and codebases developed for TensorFlow 1.5. - Python 3.6 Support: Ensures compatibility with a wide range of Python libraries and tools. - NVIDIA GPU Optimization: Utilizes CUDA 9.1 to leverage GPU acceleration, enhancing computational performance. - Ubuntu Operating System: Provides a stable and widely-used Linux environment for development. Primary Value and Problem Solved: This AMI addresses the complexities associated with setting up a deep learning environment by offering a pre-configured solution. Users can focus on developing and deploying machine learning models without the overhead of configuring software dependencies and ensuring hardware compatibility. By leveraging GPU acceleration through CUDA 9.1, it significantly reduces training times, making it ideal for production-level deep learning tasks.






- [View TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu pricing details and edition comparison](https://www.g2.com/products/tensorflow-1-5-python-3-6-nvidia-gpu-cuda-9-1-production-on-ubuntu/reviews?section=pricing&secure%5Bexpires_at%5D=2026-06-30+17%3A09%3A52+-0500&secure%5Bsession_id%5D=952d9e5e-2ee4-4947-bf83-431eae048049&secure%5Btoken%5D=d8f1ebdb8f854650778a2325d9bb56576e486d143c994719ba5a66bea2b7ea99&format=llm_user)

## TensorFlow 1.5 Python 3.6 NVidia GPU CUDA 9.1 Production on Ubuntu Features
**Agentic AI - AWS Marketplace**
- Autonomous Task Execution
- Multi-step Planning
- Cross-system Integration