Write for Us

How to contribute to The ML Practitioner

Photo by Tran Mau Tri Tam ✪ on Unsplash

Let’s keep this simple!

To submit, please reach out to us on LinkedIn, and send us an unpublished Medium draft link along as a short paragraph about yourself to us via chat.

If you’ve already published your article elsewhere, please reach out to us and we can make it work as well :)

We aim to get back to you in 2–3 days.

You are welcome to sign up for the Medium Partner Program to earn from your article. Alternatively, you can publish a free article which is accessible to non-members.

Some quick points to keep in mind:

1. All Medium users must follow Medium’s Rules and Terms of Service. This includes writers for The ML Practitioner, which is a Medium publication. Please read the terms before submitting your article.
2. The ML Practitioner also follows Medium’s Curation Guidelines. This means that articles submitted to The ML Practitioner must be of high quality and meet Medium’s guidelines in order to be published.

On style:

1. Write a story that needs to be told. This could be a new idea, a new way of doing things, or a unique perspective on an existing topic.
2. Have a clear message. State your main point in the introduction and support it with evidence throughout the article.
3. Persuade your audience. Use logical arguments, examples, and data to convince readers that your ideas are valid.
4. Use clear and concise language. Avoid jargon and technical terms that your readers may not understand.
5. Include visuals. Images, graphs, and GIFs can help to illustrate your points and make your article more engaging.
6. Check for grammar, spelling, and punctuation errors before you send us your work for final edits.
7. Use Unsplash and copyright-free images only.
8. If necessary, cite your sources in the bottom of the article.

Potential Topics

Please make sure your article is in line with one of the following topics:

• Machine learning algorithms and techniques: This topic could include articles on:
  - The different types of machine learning algorithms and how they work
  - How to choose the right machine learning algorithm for a given task
  - How to implement and train machine learning models
  - How to evaluate and improve machine learning models
• MLOps best practices: This topic could include articles on:
  - How to build and deploy machine learning models in production
  - How to monitor and maintain machine learning models
  - How to version and track machine learning models
  - How to collaborate on machine learning projects
• Real-world case studies: This topic could include articles on:
  - How machine learning is being used in different industries and applications
  - The benefits and challenges of using machine learning in the real world
  - Lessons learned from real-world machine learning projects
• Industry trends and insights: This topic could include articles on:
  - The latest trends in machine learning research and development
  - The growing adoption of machine learning in different industries
  - The impact of machine learning on society and the economy
• Responsible AI: This is a broader topic that encompasses AI ethics, but also includes other aspects of developing and using AI in a responsible way, such as fairness, accountability, and transparency.
• AI for social good: This topic focuses on how AI can be used to solve real-world problems and improve people’s lives. Examples of articles on this topic could include:
  - How AI is being used to improve healthcare
  - How AI is being used to develop sustainable energy solutions
  - How AI is being used to improve education
• AI for business: This topic focuses on how AI can be used to improve business operations and create new products and services. Examples of articles on this topic could include:
  - How AI is being used to improve customer service
  - How AI is being used to automate tasks
  - How AI is being used to develop new products and services
• AI and the future of work: This topic explores how AI is changing the way we work and what the future of work looks like in the age of AI. Examples of articles on this topic could include:
  - What jobs will be replaced by AI?
  - What new skills will be needed in the age of AI?
  - How can we ensure that everyone benefits from AI?