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#neural-forecast
Title
# neural-forecast
c

Chris Gervais

10/04/2022, 7:41 PM
what's the recommended way to generate a prediction dataframe in
v1.0.0
? it looks like we should always be using the
core.NeuralForecast
wrapper now instead of using the model predict methods directly - is that correct?
k

Kin Gtz. Olivares

10/04/2022, 8:50 PM
That is correct
f

fede (nixtla) (they/them)

10/04/2022, 9:19 PM
hey @Chris Gervais! As Kin mentioned, you’re right. The new syntax allows fitting multiple models without defining a dataset/loader for each of them. Also, the main idea behind
NeuralForecast
is that input and output are dataframes. You can find an example here: https://nixtla.github.io/neuralforecast/examples/getting_started_with_nbeats_and_nhits.html. Please let us know your thoughts about the new interface and if you have further questions.
m

Max (Nixtla)

10/04/2022, 10:29 PM
Hi @Chris Gervais, as you noticed, we have been working on a new version of NeuralForecast to make usage easier. We would love for you to play around and tell us if you want or need something. New Exciting Features: * Updated Getting Started: https://nixtla.github.io/neuralforecast/examples/getting_started_with_nbeats_and_nhits.html * Unified interface for training and predicting * Classes for automatic hyperparameter optimization for different models: https://nixtla.github.io/neuralforecast/models.html * Multi Quantile Forecast * Out of the Box GPU Support * Unified Datasets/Dataloader class for all models * Support for different hyperopt backends * Pytorch lighting support
c

Chris Gervais

10/05/2022, 12:43 PM
awesome, yah so far so good! we're tuning on our end but passing a single model to the wrapper seems to be working well. i did notice a change to the license though that appears to prohibit any commercial use of the library, do you happen to have any more details on the implications of https://github.com/Nixtla/neuralforecast/pull/285/files?
m

Max (Nixtla)

10/05/2022, 2:06 PM
You can still use the library for basically whatever purpose you want. It’s the same Apache license + one specific restriction.
Copy code
May I create, distribute, offer as SaaS, and/or "sell" my products using Commons Clause licensed components?
Yes!

Commons Clause only forbids you from "selling" the Commons Clause software itself. You may develop on top of Commons Clause licensed software (adding applications, tools, utilities or plug-ins) and you may embed and redistribute Commons Clause software in a larger product, and you may distribute and even "sell" (which includes offering as a commercial SaaS service) your product. You may even provide consulting services (see clarifying discussion here). You just can't sell a product that consists in substance of the Commons Clause software and does not add value.

This is not a new concept. It's similar to "value-add" requirements in many licenses. For example let's say you use a library containing numerical algorithms from Rogue Wave Software. Can you create an application with the library and sell the application? Yes. Can you offer that application as SaaS and charge for it? Yes. Can you change the name of the library and change some function names and sell the library or offer it as SaaS? No.

Let's apply the example to Commons Clause licensed software. Commons Clause-licensed Redis Graph is a graph database module for BSD-licensed Redis. Can you create applications with Redis Graph and distribute and/or sell them? Yes. Can you redistribute Redis Graph along with your application? Yes. Can you offer that application as SaaS and charge for it? Yes. Can you take Redis Graph itself, call it ElastiGraph and offer it as SaaS and charge for it. No.
Here is a complete FAQ: https://commonsclause.com/
Does that makes sense @Chris Gervais?
c

Chris Gervais

10/05/2022, 2:09 PM
Gotchya, yep that makes perfect sense. I may follow up in a few days with clarifying questions but I think that clears things up
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