Machine Learning Playground VS Neuro

Compare Machine Learning Playground VS Neuro and see what are their differences

Daily AI sports picks generated by artificial intelligence. SafeBet.ai helps you analyze all NBA, NFL, MLB, UFC and soccer games. It has a massive database by having analyzed all the games in the past 3 years. Use AI to improve your sports bets. featured

Contents:

» Base Details
» Videos
» Reviews
» Alternatives

Machine Learning Playground

Breathtaking visuals for learning ML techniques.

Neuro

Instant infrastructure for machine learning

Landing page //
2019-02-04

Landing page //
2021-12-03

Machine Learning Playground

Categories	AI Developer Tools Data Science And Machine Learning APIs
Website	ml-playground.com

Edit details

Neuro

Categories	APIs Developer Tools AI Data Science And Machine Learning
Website	getneuro.ai

Edit details

Machine Learning Playground videos

+ Add

Machine Learning Playground Demo

Neuro videos

+ Add

High Yield Neurology Review for Step 2 CK & Shelf Exam

Category Popularity

0-100% (relative to Machine Learning Playground and Neuro)

Machine Learning Playground

Neuro

84 84%

16% 16

Developer Tools

80 80%

Developer Tools

20% 20

Data Science And Machine Learning

84 84%

Data Science And Machine Learning

16% 16

APIs

0 0%

APIs

100% 100

User comments

Share your experience with using Machine Learning Playground and Neuro. For example, how are they different and which one is better?

Social recommendations and mentions

Based on our record, Neuro seems to be more popular. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Machine Learning Playground mentions (0)

We have not tracked any mentions of Machine Learning Playground yet. Tracking of Machine Learning Playground recommendations started around Mar 2021.

Neuro mentions (4)

Is there any practical way or roadmap to learn ML without all the backstage things like theorems,proofs in maths etc. , Like learning how to use ML libraries and frameworks and deploy models?
Projects are definitely the best way to learn models. Build things for fun that do things in topics/fields that you care about or think is cool. a few years ago when I was getting into ML stuff I build fantasy football things that weren't even useful but provided an actual use case. Then I did more complicated stuff with photography and lighting because I did real estate photography. As far as ML libraries go,... Source: almost 3 years ago
[D] Serverless GPU?
So far I’ve seen AWS Sagemaker kind of allows for a situation like this, but would rather not deal with all that config. Algorithmia and Nuclio are too enterprise focused. Neuro is new and looks great, but from my understanding I would still need to create a lambda instance myself that then calls neuro’s servers - too indirect. Is there a total solution out there for this? Source: almost 3 years ago
[P] Silero NLP streaming on serverless GPUs (~300ms latency)
A couple of weeks ago I put out a post on DeepSpeech running on the serverless setup at Neuro (https://getneuro.ai), and I've now got Silero running there as well. I've found this model is a lot faster than DS and way more accurate. Seeing around 300ms per request at the moment, hopefully will be closer to 100ms soon but this is a pretty decent speed in this application already. Source: about 3 years ago
[P] Deepspeech streaming to serverless GPUs
I just made a streaming script connecting Deepspeech to serverless GPUs at Neuro (https://getneuro.ai). Was a fun piece of work, and cool to play around with. You can find the source here: https://github.com/neuro-ai-dev/npu_examples/tree/main/deepspeech. Source: about 3 years ago