Publish and monetize your notebooks

Create your notebooks (Jupyter, Colab or others) as usual and then deploy it here, share it with our audicence and make money from subscriptions.

How it Works? or Create Publication
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Notebook categories

The notebooks you'll create here will be focused on these categories

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Newsletters

As a writer you can upload notebooks with the frequency you want. Like daily, bi-weekly or weekly

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Tutorials

You can upload notebooks written in the shape of tutorials to teach things about data science

For Writers

Build an audience and a personal brand around your notebooks.

  • Write high-quality, highly technical content supported by narrative text on notebooks

  • Create your notebooks (Jupyter, Colab or others) as usual and then upload it here and share it with our audicence

  • Build an audience by writing about what you are passionate about and build your personal brand

Highly technical content, written in a familiar format (notebooks) along with narrative text


FAQ's

You, as a data science expert, can create a publication. Each publication has a unique name. An author can only create "one" publication. The author of a publication can create as many notebooks as he wants and as often as he wants (daily, bi-weekly or weekly).
Yes, but only if they have an active subscription. If the reader has an active subscription he/she will be able to download all the current notebooks and datasets from the platform and new notebooks as they are published.
Yes, the reader will be able to access all notebooks and datasets hosted in the platform.
Each month we add up the value of all the subscriptions paid by readers and divide them among all the writers in the proportions in which their datasets are downloaded. The more downloads from your notebooks, the more you earn!
High quality content is required for all Notebooks, mainly content written in a narrative way, with understandable and self-explanatory code, related to data science and mostly highly technical content. This is a great example of how notebooks should be built:
Yes, we review the content that is published on the platform, always ensuring the fulfillment of high standards of quality and narrative.
Generally speaking, highly technical notebooks are requested on topics for all levels, with images, narrative and explanatory text of the code's intention. It is highly advisable to provide links to datasets and resources of interest within the notebook. This is a great example of how notebooks should be built:
Data Science, Data Analysis, Machine Learning, Deep Learning and Data Engineering are the central topics of our audience.
Unlike other sites such as Towards Data Science or other data science-related blogs, NarrativeText.co aims to make it easy to create content in a format familiar to data scientists: through notebooks. This also allows for greater understanding and replicability of the code by readers. Last but not least, the possibility of having recurring paid subscribers to your exclusive content.
Subscribers who pay for a monthly or annual subscription expect frequent content creation. The minimum recommended for a publication is to have at least one notebook per week. The higher the frequency, the more engagement and value for the reader, the less churn and the higher LTV (Long Time Value) for you as an author.
Soon we will have an automated process, for now every month we close books and send the corresponding money to each author, regardless of the country of residence. The transfer cost is assumed by the author.
At the publication level you can only create one, and within it you can have as many notebooks as you want. Each publication has a unique name, a logo, and a description that allows you (and allow readers) to identify it from the others.
Within your publication, you can create as many notebooks as you want. The most important thing is the consistency and quality of them.
Yes, in the dashboard of the site, you can see at any moment the number of visits that your notebooks have, the subscribers, and the number of downloads. You will also be able to see the comments of the notebooks that readers make and the reviews that subscribers leave.
Yes, you'll be only allowed to create content related to data science.
If you have a non-English speaking audience you can also create notebooks (title, subtitle and content) in any of the following languages: Hindi, Spanish, French, Mandarin, German, Arabic, Russian and many more.
We are constantly creating new audiences, with our own marketing efforts. However, this is a win-win situation, so if you have your own email list, social networks or audience, it is a good idea that you can provide yourself by sharing links from your notebooks. Remember that you can make money from your publication!

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Technical questions

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Revolutionizing the way notebooks are consumed!

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