Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Read by thought-leaders and decision-makers around the world. Phone Number: +1-650-246-9381 Email: [email protected]
228 Park Avenue South New York, NY 10003 United States
Website: Publisher: https://towardsai.net/#publisher Diversity Policy: https://towardsai.net/about Ethics Policy: https://towardsai.net/about Masthead: https://towardsai.net/about
Name: Towards AI Legal Name: Towards AI, Inc. Description: Towards AI is the world's leading artificial intelligence (AI) and technology publication. Founders: Roberto Iriondo, , Job Title: Co-founder and Advisor Works for: Towards AI, Inc. Follow Roberto: X, LinkedIn, GitHub, Google Scholar, Towards AI Profile, Medium, ML@CMU, FreeCodeCamp, Crunchbase, Bloomberg, Roberto Iriondo, Generative AI Lab, Generative AI Lab VeloxTrend Ultrarix Capital Partners Denis Piffaretti, Job Title: Co-founder Works for: Towards AI, Inc. Louie Peters, Job Title: Co-founder Works for: Towards AI, Inc. Louis-FranΓ§ois Bouchard, Job Title: Co-founder Works for: Towards AI, Inc. Cover:
Towards AI Cover
Logo:
Towards AI Logo
Areas Served: Worldwide Alternate Name: Towards AI, Inc. Alternate Name: Towards AI Co. Alternate Name: towards ai Alternate Name: towardsai Alternate Name: towards.ai Alternate Name: tai Alternate Name: toward ai Alternate Name: toward.ai Alternate Name: Towards AI, Inc. Alternate Name: towardsai.net Alternate Name: pub.towardsai.net
5 stars – based on 497 reviews

Frequently Used, Contextual References

TODO: Remember to copy unique IDs whenever it needs used. i.e., URL: 304b2e42315e

Resources

Take our 85+ lesson From Beginner to Advanced LLM Developer Certification: From choosing a project to deploying a working product this is the most comprehensive and practical LLM course out there!

Publication

11 Docker Container Images for Generative AI & ML Projects
Data Science   Latest   Machine Learning

11 Docker Container Images for Generative AI & ML Projects

Author(s): Youssef Hosni

Originally published on Towards AI.

11 Docker Container Images for Generative AI & ML Projects

Docker containers offer significant advantages for machine learning by ensuring consistent, portable, and reproducible environments across different systems.

By encapsulating all dependencies, libraries, and configurations in a container, Docker eliminates compatibility issues and the β€œit works on my machine” problem.

This makes it easier to move ML projects between development, cloud, or production environments without worrying about differences in setup. Additionally, Docker enables scalability and isolation, allowing machine learning workflows to be easily scaled using tools like Kubernetes, and ensuring that dependencies do not conflict between different projects.

In this article, we will explore 11 Docker container images for Generative AI and machine learning projects. These include tools for development environments, deep learning frameworks, machine learning lifecycle management, workflow orchestration, and large language models.

I. Machine Learning & Data Science

PythonJupyter Notebook data science stack

II. Generative AI & Deep Learning

3. Hugging Face Transformers

4. NVIDIA CUDA deep learning runtime

5. TensorFlow

6. PyTorch

7. Ollama

8. Qdrant

III. Workflow Orchestration & ML Lifecycle Management

9. Airflow

10. MLflow

11. Kubeflow Notebooks

Most insights I share in Medium have previously been shared in my weekly newsletter, To Data & Beyond.

If you want to be up-to-date with the frenetic world of AI while also feeling inspired to take action or, at the very least, to be well-prepared… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming aΒ sponsor.

Published via Towards AI

Feedback ↓