KRkristianp·Jan 28, 2020Submission
Turi Create simplifies the development of custom machine learning models
4 points · Open discussionapple
turicreate
C++2017–2020
apple / turicreate · Archived
turicreate
Turi Create simplifies the development of custom machine learning models.
8Distinct people
9Mentions
0Explicit recommenders
11.2KGitHub stars
What to know before exploring
What it is
Turi Create simplifies the development of custom machine learning models.
GitHub
Where it is used
No documented product use has been verified yet.
What people are saying
No recommendation phrase was found in the indexed comments.
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Also in these discussions
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This week on Hacker News
Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 5:04:57 PM UTC.
No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.
Mentions over time
HN mentions by month9 dated mentions
Observed mentions: 2017-12-08 22:08:41 UTC to 2020-01-28 03:16:24 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| Dec 2017 | 2017-12-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 2 | 1 | 1 |
| Jan 2018 | 2018-01-01 00:00:00 UTC | 2018-02-01 00:00:00 UTC | 0 | 0 | 0 |
| Feb 2018 | 2018-02-01 00:00:00 UTC | 2018-03-01 00:00:00 UTC | 1 | 0 | 1 |
| Mar 2018 | 2018-03-01 00:00:00 UTC | 2018-04-01 00:00:00 UTC | 1 | 0 | 1 |
| Apr 2018 | 2018-04-01 00:00:00 UTC | 2018-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2018 | 2018-05-01 00:00:00 UTC | 2018-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2018 | 2018-06-01 00:00:00 UTC | 2018-07-01 00:00:00 UTC | 1 | 0 | 1 |
| Jul 2018 | 2018-07-01 00:00:00 UTC | 2018-08-01 00:00:00 UTC | 0 | 0 | 0 |
| Aug 2018 | 2018-08-01 00:00:00 UTC | 2018-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2018 | 2018-09-01 00:00:00 UTC | 2018-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2018 | 2018-10-01 00:00:00 UTC | 2018-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2018 | 2018-11-01 00:00:00 UTC | 2018-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2018 | 2018-12-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2019 | 2019-01-01 00:00:00 UTC | 2019-02-01 00:00:00 UTC | 1 | 0 | 1 |
| Feb 2019 | 2019-02-01 00:00:00 UTC | 2019-03-01 00:00:00 UTC | 0 | 0 | 0 |
| Mar 2019 | 2019-03-01 00:00:00 UTC | 2019-04-01 00:00:00 UTC | 0 | 0 | 0 |
| Apr 2019 | 2019-04-01 00:00:00 UTC | 2019-05-01 00:00:00 UTC | 0 | 0 | 0 |
| May 2019 | 2019-05-01 00:00:00 UTC | 2019-06-01 00:00:00 UTC | 0 | 0 | 0 |
| Jun 2019 | 2019-06-01 00:00:00 UTC | 2019-07-01 00:00:00 UTC | 0 | 0 | 0 |
| Jul 2019 | 2019-07-01 00:00:00 UTC | 2019-08-01 00:00:00 UTC | 1 | 0 | 1 |
| Aug 2019 | 2019-08-01 00:00:00 UTC | 2019-09-01 00:00:00 UTC | 0 | 0 | 0 |
| Sep 2019 | 2019-09-01 00:00:00 UTC | 2019-10-01 00:00:00 UTC | 0 | 0 | 0 |
| Oct 2019 | 2019-10-01 00:00:00 UTC | 2019-11-01 00:00:00 UTC | 0 | 0 | 0 |
| Nov 2019 | 2019-11-01 00:00:00 UTC | 2019-12-01 00:00:00 UTC | 0 | 0 | 0 |
| Dec 2019 | 2019-12-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 0 | 0 | 0 |
| Jan 2020 | 2020-01-01 00:00:00 UTC | 2020-02-01 00:00:00 UTC | 2 | 1 | 1 |
What Hacker News says
9 sourcesHas anyone here compared Turi Create with pandas and numpy recently? It was open-sourced by apple: https://github.com/apple/turicreate
Seems like it's good for creating ml models and deploying them to apple devices.
In PandaPy has the speed of NumPy and the usability of Pandas30 seconds googling yields....Amazon (https://aws.amazon.com/blogs/machine-learning/amazons-own-ma...), Apple (https://opensource.apple.com/, https://github.com/apple/turicreate)
In Google AI Education Resources+1 for this recommendation, but it's called turicreate now and can be found here: https://github.com/apple/turicreate
In Show HN: A tool to find related subredditsThis will appeal to any developer that wants to deploy machine learning models on macOS or iOS and get the most out of the hardware (Metal w/Core ML).
> The docs [1] also seem to imply they're using transfer learning from more robust models for their image classifier
I read that as a recommendation for the minimum number of training samples per label (e.g. 10 photos w/leopard tagged).
Apple's Turi Create [1] also also been getting some love these last few months to add support for exporting to Core ML.
[1] https://github.com/apple/turicreate
In Create MLAbout a year ago, a sales guy from SAS came to give a talk about Viya at our uni. They even brought a data scientist (whom I believe was actually a smart kid and feeling uneasy about being dragged into a sales pitch). Traditionally, SAS has pushed a lot of resources in the educational sector. Get them started young, and they'll be customers forever.
So anyway, the presentation includes showing off a Jupyter notebook and showing how you can easily use pandas to load in your data set, build a model (with Viya), and plot the results with matplotlib. Standard data science stuff, but distributed automagically thanks to Viya.
During the QA, I asked the following questions:
- So you are basically attempting the same as what Spark has done, and are just using R/Python/... as a client? Yes, but we're way more powerful, manageable, etc...
- Can I s
Read the rest
ee the source code of your models, or build new ones myself? No... well maybe, you can write them in SAS base and call them.
- Can I at least export the model to something like PMML? Oh yes you can export (shows this off)... to SAS base code.
- Do you have GPU support for those fancy convolutional neural networks? No (although I've heard this has changed, though I would still put my trust more towards Tensorflow or Pytorch).
It kind of seems like a last attempt to get some new lock-in going. Even Apple's re-open sourcing of turi (https://github.com/apple/turicreate) is more honest (and more powerful, actually).
I like SAS, they have some very smart people working there and some great consultants (PhD's, often), but there's too much sales going on. This is what killed IBM as well.
You can also consider using creating a model using the Activity Classifier toolkit in Turi Create which automatically exports in CoreML format for use in. your watchOS app
https://github.com/apple/turicreate/tree/master/userguide/ac...
In Introduction to Apple WatchKit with Core Motion – Tracking Jumping JacksTuri Create simplifies the development of custom machine learning models
179 points · Open discussion