How to become a FloydHub A.I. Writer

TLDR: Apply now, write insanely great tutorials, and get paid in GPU credit (or πŸ’΅)

TLDR: Apply now, write insanely great tutorials, and get paid in GPU credit (or πŸ’΅)

We're building the world's best blog for practical, real-world tutorials of groundbreaking A.I. techniques.

In fact, you've probably already read some of our more popular posts – like this one from Emil Wallner:

Or perhaps this one from Sam Lynn-Evans :

Both of these posts were written by members of our FloydHub community, and they've gone on to inspire people hungry for practical, real-world tutorials in AI.

We're looking for a few more writers to join us and create even more insanely great tutorials!

Whether you're fresh-faced or old-and-crusty in the ways of data science, we're excited to work with you to generate amazing articles for our community. You'll have all the support you need to write something awesome and make a dent in the AI universe.

Your mission, should you choose to accept, Β is to craft an article-length tutorial for a project relating to one of these categories:

  • Deep learning
  • Machine learning
  • Artificial intelligence
  • Natural language processing
  • Computer vision
  • Data science

Once you're accepted into the FloydHub AI Writers program, we'll provide more details and assistance to help you get started with your first post on the FloydHub Blog. Here's a few more reasons the FloydHub AI Writers program rocks:

  • Editing and proofreading support, from the best there is
  • Feedback and guidance for your deep learning and machine learning projects
  • Promotion of your post to our 100K+ readers
  • Building your personal brand in data science

Show off your skillz! Get better at writing! Click this button! Be amazing!

Important: given the high number of applicants, we have paused the call for AI writers. If you are interested, you can still apply, but it can take several months before get back to you.

"Psst! Need inspiration?!" We are currently looking for writers for these topics:

  • Out Of Memory Error - what you can do to fix it
  • Mixed Precision Training - Training faster with Tensor Cores
  • Data Augmentation for PyTorch, TensorFlow & Keras
  • TensorFlow vs PyTorch
  • Real Time-Object Detection with Yolo Darknet
  • Evaluation metrics: Precision, Recall, ROC, etc...
  • Object Detection Frameworks comparison
  • 10 Trends in Deep Learning Computer Vision
  • Data pipeline for (Video, Text, Images, etc...)

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