Show HN: 1000 GitHub Data Science projects, now executable in 1 click
cloud.blobcity.com
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1. I’m glad this is the most upvoted comment in order to provide visibility and
2. I’m glad the founder wants to make it right apparently by having the alleged freelancer send details to rectify
but the the fact that the founder doesn’t immediately refute that this occurred and only wants to now potentially make it right by having the freelancer send his details over to get paid is very troubling for me. I hope this comes out as a false allegation but if not I wouldn’t want to support this at all.
A: five years ago you made a pretty bad mistake that hurt me personally.
B: I must have let my priorities slip, and it sounds like in my oversight I hurt you personally. Reach out with more details and we can make this right.
or
A: five years ago you made a pretty bad mistake that hurt me personally.
B: I don't really make mistakes like that.
saying a metaphorical “fuck you, I can’t pay you for the work you did for my business” by ignoring OPs alleged many emails and correspondence to get compensated is just as bad if not worse than a literal “fuck you, I can’t pay you” imo, but I’m also one that appreciates honesty and not sketchiness or being ghosted even if the outcome is not in my favor.
Your character is at stake here and again, a sleezy ghosting for years is almost certainly worse I assume for most people than a phone call, email, whatever to tell someone you unfortunately just can’t afford to pay them right now but will as soon as you can. That’s the biggest issue here.
Why would you assume for there to be no proper conclusion? It is not like running away from the truth helps anyone. Is it not obvious that anyone would inform of payment delays, non-payment against dissatisfactory services, etc? What’s there to gain by not informing? It is not like these things don’t happen, because they do happen. Often more times than you did like.
I would like to take this claim at face value and just assume it to be true that a payment was not made. If its a troll, it would be a really sad one. Going forward under this assumption, the freelancer certainly thinks that he/she should have got paid for the services delivered. This is where a communication gap could exist. I highly doubt we have not properly closed an engagement. It is more likely it was closed against the interest of the freelancer, and the freelancer won’t take NO for an answer, and is now making a claim under an incorrect pretex.
What would you advise as the best course of action in such a scenario?
I wouldn’t and am not. It’s your responsibility to confirm one way or the other.
If this is a case of a disgruntled freelancer who isn’t getting more than what he/she wants even under a contractual and agreed upon arrangement, then I’ll gladly retract from my former concerns and sincerely apologize for my personal issues towards the matter.
But if this is almost literally anything else where the freelancer did work and wasn’t compensated under the terms of a contractual agreement, I will hold up my concern and maintain my disdain towards the matter.
Data Science models, today are scattered, and as an engineer and architect of systems, I’ve personally experienced, there is a lot of time spent on trying out the right models, versioning, collaboration and execution. Not everything works alongside everything. We’ve now made this achievable by running a cloud infrastructure where you can not only explore the DS projects, but also run it on the cloud with 1-click. Collaborate with your fellow team mates and work together on a ready Jupyter ecosystem together.
Here are some key things to know:
• Explore and run, 1000+ GitHub projects on the cloud
• Unlimited open source Cloudbooks for free
• We have spent time and effort to curate the top projects that our team and existing users nominated for and tried to keep the UX clean and easy to use. Suggest any that you’d want to see in here, a one-click deployment worthy project.
Basically we allow users to make their own personal editable copies of the Cloudbook. When you "Run", it is first replicating the Cloudbook into your account and then running. You can edit the code in your copy without affecting the main Cloudbook. Free unlimited CPU, RAM & Storage gets included with every Cloudbook for you to make continuous edits and perform repeat runs, including long running run operations.
Not sure how we can achieve this without a registration. Do you have something in mind?
And a link to "learn more!"
Still very far from smooth (<10) click experience.
The workflow took a while to get started:
Manually create account (no external auth option such as Github?) -> verify account -> create notebook -> set pw for notebook -> run notebook
I did all that only to find that no required libraries are there.... not even Pandas?
By comparision Google Colab onboarding is much smoother and you know you are getting a working Tensorflow, Pandas, Plotly etc out the box. Sure you pay the privacy tax to Google for this smoothness.
My biases:
- I've installed and maintain Littlest Jupyter Hub instance for teammates at my organization.
- I teach using local Anaconda installation.
- I use myBinder and Google Colab.
If I did not have a smooth experience I would imagine someone starting out would have a harder time.At the very least you should curate the packages so they run out of the box, without fiddling with requirements.txt, yaml, pip install, conda etc.
Adding features:
- Login with Google & Github accounts
- Changing default type setting to "Data Science Notebook"
- A package library with one-click install
Changing features: - Simpler UX (reduced clicks required)
- Removing the mandatory plan selection - Starting every user on free plan by default
Anything else you recommend we should do?You can create your own Cloudbooks and use our unlimited infra for your next AI experiment.
If your code & data is open, our infra is free for you. If your code & data is private, then plans start at just $25/m. GPU's are available on the $75/m and $150/m plan. Do give it a try for your next AI / Data Science project.
More info here: https://blobcity.com
Something something strong claims.
That must be the closest I've seen to a self refuting claim on here in a long time. Would love to hear more about how you do either the truly unlimited part or the free part practically.
Please do give it a try. Only condition, your code & data must be open source if you want it on the free plan. Else you can take a paid plan. Unlimited part remains the same, but it won’t be free for private use.
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