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Push Jupyter notebooks to Production ⚡️ with 5 low code formulas
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#naas #notebooks #lowcode #opensource
✊⚡️Pushing notebooks to production should not be so hard!
When you work on Excel, everything you do is by default to production.
You update your spreadsheet, you share it with your audience.
That's it.
→ But when you start working on data science projects, replacing "Excel + VBA" by "Jupyter Notebooks + Python"
You NEED TO DO A LOT to push to production, and it can be quite complicated to:
🛑 convert your notebook to a python script
🛑 deploy it to on a server
🛑 set up a cron task to schedule it
🛑 ensure security
🛑 make sure the whole ecosystem works together
...when you actually want to focus on solving a business problem!
→ What if, instead, you could do that from your notebooks?
With Naas notebooks, you can do that with minimum technical skills.
You only need to master those 5 low code features:
(1) ⏰ Scheduler
(2) 🛎️ Notification
(3) 🖼️ Asset
(4) ⚙️ Webhook
(5) 🔗 Dependency
→ What are the benefits?
Imagine you need to produce an analysis of Tesla's (TSLA) stock price, use ML to predict +20days lines, and deliver it by email every day automatically.
This is only one example.
With Naas, you CAN DO A LOT, without so many headaches.
👉 In this video, try the awesome-notebooks repository that will make you understand how it works.
Just click on "Open in Naas" button to open the notebook (if you don't have an account, it creates one for you, and it's 100% free)
↓
Input your email
↓
Run the notebook.
It will copy the notebook in naas "⚡ → Production" folder to be executed daily.
↓
Do you find this useful? ...
🙏 Thanks a lot for the support.
💬 Comments are welcome, tell me what kind of use case you want to see next.
PS: we're working hard to build Naas, and need more help! If you know anybody who would like to contribute to open source, please let us know and tell your friends!
✊⚡️Pushing notebooks to production should not be so hard!
When you work on Excel, everything you do is by default to production.
You update your spreadsheet, you share it with your audience.
That's it.
→ But when you start working on data science projects, replacing "Excel + VBA" by "Jupyter Notebooks + Python"
You NEED TO DO A LOT to push to production, and it can be quite complicated to:
🛑 convert your notebook to a python script
🛑 deploy it to on a server
🛑 set up a cron task to schedule it
🛑 ensure security
🛑 make sure the whole ecosystem works together
...when you actually want to focus on solving a business problem!
→ What if, instead, you could do that from your notebooks?
With Naas notebooks, you can do that with minimum technical skills.
You only need to master those 5 low code features:
(1) ⏰ Scheduler
(2) 🛎️ Notification
(3) 🖼️ Asset
(4) ⚙️ Webhook
(5) 🔗 Dependency
→ What are the benefits?
Imagine you need to produce an analysis of Tesla's (TSLA) stock price, use ML to predict +20days lines, and deliver it by email every day automatically.
This is only one example.
With Naas, you CAN DO A LOT, without so many headaches.
👉 In this video, try the awesome-notebooks repository that will make you understand how it works.
Just click on "Open in Naas" button to open the notebook (if you don't have an account, it creates one for you, and it's 100% free)
↓
Input your email
↓
Run the notebook.
It will copy the notebook in naas "⚡ → Production" folder to be executed daily.
↓
Do you find this useful? ...
🙏 Thanks a lot for the support.
💬 Comments are welcome, tell me what kind of use case you want to see next.
PS: we're working hard to build Naas, and need more help! If you know anybody who would like to contribute to open source, please let us know and tell your friends!
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